Machine Learning is the process of teaching a computer how perform a task with out explicitly programming it. The process feeds algorithms with large amounts of data to gradually improve predictive performance.

#ai #python #100SecondsOfCode

🔗 Resources

Machine Learning Tutorials https://fireship.io/tags/machine-learning/
What is ML https://www.ibm.com/cloud/learn/machine-learning
Neural Networks https://towardsdatascience.com..../a-beginners-guide-t
ML Wiki https://en.wikipedia.org/wiki/Machine_learning

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🎨 My Editor Settings

- Atom One Dark
- vscode-icons
- Fira Code Font

Topics Covered

- Convolutional Neural Networks
- Machine Learning Basics
- How Data Science Works
- Big Data and Feature Engineering
- Artificial Intelligence History
- Supervised Machine Learning

** Python Certification Training: https://www.edureka.co/data-sc....ience-python-certifi **
This Edureka Live on Data Science Projects - 1 will help you understand how the processes in the data science life cycle can be used to derive insights from a given dataset.
Following topics will be discussed in this session:

Data Science Life Cycle
Projects To Take As A Beginner
COVID-19 Italy Data Analysis

Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s

#PythonEdureka #Edureka #datascienceproject #pythonprojects #pythonprogramming #pythontutorial #PythonTraining

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How it Works?
1. This is a 5 Week Instructor-led Online Course,40 hours of assignment and 20 hours of project work
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training, you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate!

---------------------------------
About the course

Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. For over a decade, Python has been used in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing.

Edureka's Python Certification Training not only focuses on the fundamentals of Python, Statistics and Machine Learning but also helps one gain expertise in applied Data Science at scale using Python. The training is a step by step guide to Python and Data Science with extensive hands-on. The course is packed with several activity problems and assignments and scenarios that help you gain practical experience in addressing predictive modeling problems that would either require Machine Learning using Python. Starting from basics of Statistics such as mean, median and mode to exploring features such as Data Analysis, Regression, Classification, Clustering, Naive Bayes, Cross-Validation, Label Encoding, Random Forests, Decision Trees and Support Vector Machines with a supporting example and exercise help you get into the weeds.

Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to train your machine based on real-life scenarios using Machine Learning Algorithms.

Edureka’s Python course will also cover both basic and advanced concepts of Python like writing Python scripts, sequence and file operations in Python. You will use libraries like pandas, numpy, matplotlib, scikit, and master concepts like Python machine learning, scripts, and sequence.

Why learn Python?

It's continued to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging programs is a breeze in Python with its built-in debugger.

It runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for commercial products, because of its OSI-approved open source license.

It has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that it is the " Next Big Thing " and a must for Professionals in the Data Analytics domain.



Who Should Go For This Course?



Programmers, Developers, Technical Leads, Architects
Developers aspiring to be a ‘Machine Learning Engineer'
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Machine Learning (ML) Techniques
Information Architects who want to gain expertise in Predictive Analytics
'Python' professionals who want to design automatic predictive models

For more information, please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775

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This Decision Tree in the Machine Learning tutorial will help you understand all the basics of the Decision Tree and how the Decision Tree algorithm works. In the end, we will implement a Decision Tree algorithm in Python on loan payment prediction. This Decision Tree tutorial is ideal for both beginners as well as professionals who want to learn Machine Learning Algorithms.

Below topics are covered in this Decision Tree Algorithm Tutorial:
0. Intro (0:00)
1. What is Machine Learning? ( 02:25 )
2. Types of Machine Learning? ( 03:27 )
3. Problems in Machine Learning ( 04:43 )
4. What is a Decision Tree? ( 06:29 )
5. What are the problems a Decision Tree Solves? ( 07:11 )
6. Advantages of Decision Tree ( 07:54 )
7. How does Decision Tree Work? ( 10:55 )
8. Use Case - Loan Repayment Prediction ( 14:32 )

Dataset Link - https://drive.google.com/drive..../folders/1JybOOdRsMY

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⏩ Check out the Machine Learning tutorial videos: https://bit.ly/3fFR4f4

Machine Learning Articles: https://www.simplilearn.com/what-is-artificial-intelligence-and-why-ai-certification-article?utm_campaign=Decision-Tree-Algorithm-With-Example-RmajweUFKvM&utm_medium=Tutorials&utm_source=youtube

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#DecisionTreeMachineLearning #DecisionTree #DecisionTreeAlgorithm #DecisionTreeAlgorithmInMachineLearning #DecisionTreePython #DecisionTrees #DecisionTreeExample #MachineLearningAlgorithms #MachineLearningTutorial #Simplilearn

What is a Decision Tree Algorithm?
A Decision Tree is a supervised machine learning algorithm for solving classification problems. Generally, a decision tree is drawn upside down with its root at the top and it is known as the Top-Down Approach. Decision trees are used for handling non-linear data sets effectively. The decision tree tool is used in real life in many areas, such as engineering, civil planning, law, and business.

➡️ About Artificial Intelligence Engineer

This Artificial Intelligence Engineer course Created in partnership with IBM, this course introduces students to blended learning and prepares them to be AI and Data Science specialists. In Armonk, New York, IBM is a significant cognitive service and integrated cloud solution firm that provides many technology and consulting solutions.
IBM is a leader in AI and Machine Learning technology verticals for 2021. This AI masters course will prepare students for Artificial Intelligence and Data Analytics careers.

✅ Key Features
- Add the IBM Advantage to your Learning
- 25 Industry-relevant Projects and Integrated labs
- Immersive Learning Experience
- Simplilearn's JobAssist helps you get noticed by top hiring companies

✅ Tools Covered
- ChatGPT
- Flask
- Matplotlib
- django
- Python
- Numpy
- Pandas
- SciPy
- Keras
- OpenCV
- And Many More…

👉Learn More at: https://www.simplilearn.com/iitk-professional-certificate-course-data-analytics?utm_campaign=MachineLearning-RmajweUFKvM&utm_medium=Description&utm_source=youtube


🔥 Enroll for FREE Machine Learning Course & Get your Completion Certificate: https://www.simplilearn.com/learn-machine-learning-basics-skillup?utm_campaign=MachineLearning&utm_medium=Description&utm_source=youtube

Learn more about Data Pipelines → https://ibm.biz/BdPEPM

Data is a lot like water; it often needs to be refined as it travels between a source and its final destination. That’s where data pipelines come in – they merge, filter, and summarize raw data, providing the end user with a clean product to analyze. Luv Aggarwal, a Data Solution Engineer at IBM, explains how several processes often embedded within data pipelines – like ETL, replication, virtualization, machine learning, and batch processing – help generate actionable business intelligence.

Get started with IBM Cloud free of charge → https://ibm.biz/BdPEPS

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#Data #DataPipelines #DataAnalyses #DataIntegration #BusinessIntelligence #ETL

🔥 Data Science Training (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎") - https://www.edureka.co/data-sc....ience-r-programming-
This Machine Learning Algorithms Tutorial shall teach you what machine learning is, and the various ways in which you can use machine learning to solve a problem! Towards the end, you will learn how to prepare a data-set for model creation and validation and how you can create a model using any machine learning algorithm! In this Machine Learning Algorithms Tutorial video you will understand:

1) What is an Algorithm?
2) What is Machine Learning?
3) How is a problem solved using Machine Learning?
4) Types of Machine Learning
5) Machine Learning Algorithms
6) Demo


You can also check out this Machine Learning with Python video for more insights: https://youtu.be/nJKxWbQ1jaw

Check our complete Data Science playlist here: https://goo.gl/60NJJS

Subscribe to our channel to get video updates. Hit the subscribe button above.

#Edureka #MachineLearningAlgorithms #Datasciencetutorial #Datasciencecourse #datascience

How it Works?

1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. You will get Lifetime Access to the recordings in the LMS.
4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate!

- - - - - - - - - - - - - -

About the Course

Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities.

- - - - - - - - - - - - - -

Why Learn Data Science?

Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework.

After the completion of the Data Science course, you should be able to:
1. Gain insight into the 'Roles' played by a Data Scientist
2. Analyse Big Data using R, Hadoop and Machine Learning
3. Understand the Data Analysis Life Cycle
4. Work with different data formats like XML, CSV and SAS, SPSS, etc.
5. Learn tools and techniques for data transformation
6. Understand Data Mining techniques and their implementation
7. Analyse data using machine learning algorithms in R
8. Work with Hadoop Mappers and Reducers to analyze data
9. Implement various Machine Learning Algorithms in Apache Mahout
10. Gain insight into data visualization and optimization techniques
11. Explore the parallel processing feature in R

- - - - - - - - - - - - - -

Who should go for this course?

The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course:

1. Developers aspiring to be a 'Data Scientist'
2. Analytics Managers who are leading a team of analysts
3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics
4. Business Analysts who want to understand Machine Learning (ML) Techniques
5. Information Architects who want to gain expertise in Predictive Analytics
6. 'R' professionals who want to captivate and analyze Big Data
7. Hadoop Professionals who want to learn R and ML techniques
8. Analysts wanting to understand Data Science methodologies

For more information, Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll free).

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Customer Reviews:

Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. "

Confused between Cybersecurity and Data Science as a career path in 2026? In this video, we compare both fields—job roles, required skills, salaries, demand, and future growth. Whether you’re aiming for a secure IT career or exploring data-driven opportunities, this guide will help you decide which path is right for you.

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This video on What is Deep Learningprovides a fun and simple introduction to its concepts. We learn about where Deep Learning is implemented and move on to how it is different from machine learning and artificial intelligence. We will also look at what neural networks are and how they are trained to recognize digits written by hand. We further look at some popular applications of Deep Learning. So, let’s dive into the world of Deep Learning with this video.

Watch more videos on Deep Learning: https://www.youtube.com/watch?v=FbxTVRfQFuI&list=PLEiEAq2VkUUIYQ-mMRAGilfOKyWKpHSip

#DeepLearning #WhatIsDeepLearning #DeepLearningTutorial #DeepLearningCourse #DeepLearningExplained #Simplilearn

Why Deep Learning?
It is one of the most popular software platforms used for Deep Learning and contains powerful tools to help you build and implement artificial neural networks.
Advancements in Deep Learning are being seen in smartphone applications, creating efficiencies in the power grid, driving advancements in healthcare, improving agricultural yields, and helping us find solutions to climate change. According to payscale.com, the median salary for engineers with Deep Learning skills tops $120,000 per year.
➡️ About Artificial Intelligence Engineer

This Artificial Intelligence Engineer course Created in partnership with IBM, this course introduces students to blended learning and prepares them to be AI and Data Science specialists. In Armonk, New York, IBM is a significant cognitive service and integrated cloud solution firm that provides many technology and consulting solutions.
IBM is a leader in AI and Machine Learning technology verticals for 2021. This AI masters course will prepare students for Artificial Intelligence and Data Analytics careers.

✅ Key Features
- Add the IBM Advantage to your Learning
- 25 Industry-relevant Projects and Integrated labs
- Immersive Learning Experience
- Simplilearn's JobAssist helps you get noticed by top hiring companies

✅ Tools Covered
- ChatGPT
- Flask
- Matplotlib
- django
- Python
- Numpy
- Pandas
- SciPy
- Keras
- OpenCV
- And Many More…

👉 Learn More At:

🔥🔥

️🔥IBM - Data Analyst - https://www.simplilearn.com/data-analyst-masters-certification-training-course?utm_campaign=bAyrObl7TYE&utm_medium=DescriptionFFF&utm_source=Youtube
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This video, Big Data In 5 Minutesby Simplilearn, will help you understand what is Big Data, the 5 V's of Big Data, why Hadoop came into existence, and what Hadoop is. You will also learn about the storage unit and processing unit of Hadoop and the implementation of Big Data through use cases. In the end, we will have a quiz on Hadoop. A massive amount of data that cannot be stored, processed, and analyzed using the traditional ways is known as Big Data. Hadoop is a framework that manages Big Data storage in a distributed way and processes it parallelly. Now, let's dive deep into this video and understand Big Data and Hadoop.

Below are the topics covered in this video.
00:00 Big Data In 5 Minutes
00:34 Data generated per minute
00:56 Classification of Big Data
02:00 How to store and process Big Data
03:11 Application of Big Data

What Is Big Data?
Big data refers to the vast volume, variety, and velocity of data that exceeds traditional processing methods. It encompasses structured, unstructured, and semi-structured data from various sources, offering valuable insights for informed decision-making. Big data requires advanced analytics and scalable infrastructure to extract patterns, optimize operations, and gain comprehensive understanding for transformative impact.

Don't forget to take the quiz at 04:03!

Watch more videos on HadoopTraining: https://www.youtube.com/watch?v=CKLzDWMsQGM&list=PLEiEAq2VkUUJqp1k-g5W1mo37urJQOdCZ

#WhatIsBigData #WhatIsHadoop #BigDataExplained #HadoopExplained #HadoopTraining #BigDataTraining #BigDataTutorial #HadoopTutorial #Simplilearn Big Data #SimplilearnHadoop #simplilearn
➡️ About Data Analyst Master’s Program
This online data analyst course will transform you into a data analytics expert. In this certification course, you will learn the latest analytics tools and techniques, how to work with SQL, the languages of R and Python, the art of creating data visualizations, and how to apply statistics and predictive analytics in a business environment.

✅ Key Features
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Industry-recognized Data Analyst Master’s certificate from Simplilearn
- Dedicated live sessions by faculty of industry experts
- Masterclasses from IBM experts
- Industry-recognized IBM certifications for IBM courses
- Ask-Me-Anything (AMA) sessions with IBM leadership
- Capstone from 3 domains and 20+ projects
- Exclusive hackathons conducted by IBM
- Lifetime access to self-paced learning content
- Program crafted to initiate your journey as a Data Analyst

✅ Skills Covered
- Data Analytics
- Statistical Analysis using Excel
- Data Analysis using Python and R
- Data Visualization Tableau and Power BI
- Linear and logistic regression modules
- Clustering using KMeans
- Supervised Learning
- Unsupervised Learning

👉 Learn More at:

🔥🔥

️🔥IBM - Data Scientist - https://www.simplilearn.com/data-science-course?utm_campaign=mkv5mxYu0Wk&utm_medium=DescriptionFFF&utm_source=Youtube
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This Data Science with Python Tutorial will help you understand what is Data Science, basics of Python for data analysis, why learn Python, how to install Python, Python libraries for data analysis, exploratory analysis using Pandas, introduction to series and dataframe, loan prediction problem, data wrangling using Pandas, building a predictive model using Scikit-Learn and implementing logistic regression model using Python. The aim of this video is to provide a comprehensive knowledge to beginners who are new to Python for data analysis. This video provides a comprehensive overview of basic concepts that you need to learn to use Python for data analysis. Now, let us understand how Python is used in Data Science for data analysis.


This Data Science with Python tutorial will cover the following topics:
00:01:25 What is Data Science?
00:02:30 Why learn Python?
00:04:54 How to install Python?
00:06:48 Python libraries for data analysis
00:09:34 Exploratory analysis using SciPy
00:10:04 Exploratory analysis using NumPy
00:10:36 Exploratory analysis using Pandas
00:21:32 Data Wrangling Using Pands
00:30:22 Data Modelling with SciKiLearn
Introduction to series and dataframe
00:47:33 Loan prediction problem

To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/S....implilearn?sub_confi

Download the Data Science career guide to explore and step into the exciting world of data, and follow the path towards your dream career: https://bit.ly/2S363Wx

You can also go through the slides here: https://goo.gl/ifQRpS

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#DataScienceWithPython #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning

➡️ About Data Science Course in collaboration with IBM

This Data Science course in collaboration with IBM propels your career to become a data scientist. Gain expertise in in-demand skills like Python, SQL, Excel, Machine Learning, Tableau, generative AI, and more. Dive deep into data interpretation nuances, master Machine Learning, and enhance programming skills to elevate your Data Science career.

Key Features
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Masterclasses from IBM experts
✅ Dedicated live sessions by faculty of industry experts
✅ Industry-recognized Data Scientist Master’s certificate from Simplilearn
✅ Industry-recognized IBM certifications for IBM courses
✅ Ask-Me-Anything (AMA) sessions with IBM leadership
✅ Capstone from 3 domains and 25+ projects
✅ Exclusive hackathons conducted by IBM
✅ Lifetime access to self-paced learning content
✅ Program crafted to initiate your journey as a Data Scientist
✅ Integrated labs for hands-on learning experience

Skills Covered
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Explainable AI
✅ Conversational AI
✅ Large Language Models
✅ Model Building and Finetuning
✅ Ensemble Learning
✅ Data Visualization
✅ Database Management

👉 Learn More At: https://www.simplilearn.com/iitk-professional-certificate-course-data-analytics?utm_campaign=Data-Science-With-Python-mkv5mxYu0Wk&utm_medium=Tutorials&utm_source=youtube

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This video on Data Analytics for Beginners covers all the basics to advance concepts of data analytics. In this video you will come across the introduction To Data Analytics and you will understand the usage and the need for data analytics. Then, you learn about the different processes in data analytics with some essential tools used to implement data analytics. Also, you will see a case study on how Walmart uses data analytics for running its business.

01:07 What is Data Analytics?
04:29 Steps involved in Data Analytics
08:05 Tools used for Data Analytics
11:58 Data Analytics Applications
14:45 Companies using Data Analytics
15:22 Walmart Case Study
18:09 Use Case Demo

⏩ Check out the Data Analytics Playlist: link: https://www.youtube.com/playli....st?list=PLEiEAq2VkUU

✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

#DataAnalyticsForBeginners #IntroductionToDataAnalytics #DataAnalytics #DataAnalyticsWithR #DataAnalyticsUsingR #Simplilearn

➡️ About Post Graduate Program In Data Analytics
This Data Analytics Program is ideal for all working professionals and prior programming knowledge is not required. It covers topics like data analysis, data visualization, regression techniques, and supervised learning in-depth via our applied learning model with live sessions by leading practitioners and industry projects.

✅ Key Features
- Post Graduate Program certificate and Alumni Association membership
- Exclusive hackathons and Ask me Anything sessions by IBM
- 8X higher live interaction in live online classes by industry experts
- Capstone from 3 domains and 14+ Data Analytics Projects with Industry datasets from Google PlayStore, Lyft, World Bank etc.
-
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Resume preparation and LinkedIn profile building
- 1:1 mock interview
- Career accelerator webinars

✅ Skills Covered
- Data Analytics
- Statistical Analysis using Excel
- Data Analysis Python and R
- Data Visualization Tableau and Power BI
- Linear and logistic regression modules
- Clustering using kmeans
- Supervised Learning

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🔥 Data Scientist Masters Program (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎"): https://www.edureka.co/masters....-program/data-scient
This Edureka video on "What is Data Science" will introduce you to the concepts of Data Science and how it is used to solve real-world problems. You will learn Data Science with an example on UBER dataset. Data science is the process of using the data to find solutions / to predict outcomes of a problem statement. Below are the topics covered in this Data Science Tutorial:

0:57 What is Data Science?
1:11 How Data Science works? : Data Science at UBER
2:06 Data Science Process
a. Business Requirements
b. Data Collection
c. Data Cleaning
d. Data Exploration and Analysis
e. Data Modelling
f. Data Validation
g. Deployment and Optimization
4:17 Data Science Applications
6:05 Who is a Data Scientist?
6:18 Data Scientist Job Trends
6:51 Data Scientist Skills

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#edureka #DataScienceEdureka #whatisdatascience #Datasciencein8minutes #Datasciencecourse #datascience

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About the Master's Program

This program follows a set structure with 6 core courses and 8 electives spread across 26 weeks. It makes you an expert in key technologies related to Data Science. At the end of each core course, you will be working on a real-time project to gain hands on expertise. By the end of the program you will be ready for seasoned Data Science job roles.

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Topics Covered in the curriculum:

Topics covered but not limited to will be : Machine Learning, K-Means Clustering, Decision Trees, Data Mining, Python Libraries, Statistics, Scala, Spark Streaming, RDDs, MLlib, Spark SQL, Random Forest, Naïve Bayes, Time Series, Text Mining, Web Scraping, PySpark, Python Scripting, Neural Networks, Keras, TFlearn, SoftMax, Autoencoder, Restricted Boltzmann Machine, LOD Expressions, Tableau Desktop, Tableau Public, Data Visualization, Integration with R, Probability, Bayesian Inference, Regression Modelling etc.

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For more information, please write back to us at sales@edureka.co or call us at: IND: 9606058406 / US: 18338555775 (toll free)

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This Machine Learning tutorial video is ideal for beginners to learn Machine Learning from scratch. By the end of this tutorial video, you will learn why Machine Learning is so important in our lives, what is Machine Learning, the various types of Machine Learning (Supervised, Unsupervised and Reinforcement learning), .

This Machine Learning tutorial will cover the following topics:
1. Life without Machine Learning ( 01:06 )
2. Life with Machine Learning ( 02:29 )
3. What is Machine Learning ( 04:35 )
4. Machine Learning Process ( 05:27 )
5. Types of Machine Learning ( 06:14 )
6. Supervised Vs Unsupervised ( 09:32 )
7. The right Machine Learning solutions ( 10:35 )
8. Machine Learning Algorithms ( 13:33 )
9. Use case - Predicting the price of a house using Linear Regression ( 23:24 )

What is Machine Learning: Machine Learning is an application of Artificial Intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.

Subscribe to our channel for more Machine Learning tutorial videos: https://www.youtube.com/user/S....implilearn?sub_confi

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➡️ About Artificial Intelligence Engineer

This Artificial Intelligence Engineer course Created in partnership with IBM, this course introduces students to blended learning and prepares them to be AI and Data Science specialists. In Armonk, New York, IBM is a significant cognitive service and integrated cloud solution firm that provides many technology and consulting solutions.
IBM is a leader in AI and Machine Learning technology verticals for 2021. This AI masters course will prepare students for Artificial Intelligence and Data Analytics careers.

✅ Key Features
- Add the IBM Advantage to your Learning
- 25 Industry-relevant Projects and Integrated labs
- Immersive Learning Experience
- Simplilearn's JobAssist helps you get noticed by top hiring companies

✅ Tools Covered
- ChatGPT
- Flask
- Matplotlib
- django
- Python
- Numpy
- Pandas
- SciPy
- Keras
- OpenCV
- And Many More…


👉 Learn More At:




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00:00:00 Introduction to Data Visualization Tutorial For Beginners
00:00:09 What is Data Visualization?
00:01:18 Benefits of Data Visualization
00:01:43 Data Visualization Considerations
00:02:22 Data Visualization Factors
00:02:52 Python Data Visualization Tool
00:03:15 Python Libraries for Data Visualization
00:03:40 MatPlotLib for Data Visualization
00:04:55 Understanding the Plot in Data Visualization
00:05:25 Steps to Create Plot
00:08:37 Controlling the Plot
00:08:51 Set Axix, Lables, and Legends
00:09:11 Alpha and Annotation
00:10:05 Multiple Plot
00:10:49 Sub-Plot
00:11:27 Layout and Spacing
00:11:45 Demo subplot
00:23:59 Types of Plots

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➡️ About Data Analyst Master’s Program
This online data analyst course will transform you into a data analytics expert. In this certification course, you will learn the latest analytics tools and techniques, how to work with SQL, the languages of R and Python, the art of creating data visualizations, and how to apply statistics and predictive analytics in a business environment.

✅ Key Features
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Industry-recognized Data Analyst Master’s certificate from Simplilearn
- Dedicated live sessions by faculty of industry experts
- Masterclasses from IBM experts
- Industry-recognized IBM certifications for IBM courses
- Ask-Me-Anything (AMA) sessions with IBM leadership
- Capstone from 3 domains and 20+ projects
- Exclusive hackathons conducted by IBM
- Lifetime access to self-paced learning content
- Program crafted to initiate your journey as a Data Analyst

✅ Skills Covered
- Data Analytics
- Statistical Analysis using Excel
- Data Analysis using Python and R
- Data Visualization Tableau and Power BI
- Linear and logistic regression modules
- Clustering using KMeans
- Supervised Learning
- Unsupervised Learning



👉 Learn More at:

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In this Lines Algebra for Data Science video we will discuss how you can unlock the power of data science and machine learning with a solid foundation in linear algebra! In this comprehensive video, we delve into the essential concepts and applications of linear algebra that are critical for data scientists and machine learning practitioners. You’ll learn about vectors, matrices, eigenvalues, and eigenvectors, and how these mathematical structures are used in algorithms for data processing, dimensionality reduction, and model optimization. Whether you're a beginner or looking to deepen your understanding, this video offers clear explanations, practical examples, and real-world applications to help you master the mathematical tools necessary for advanced data analysis and predictive modeling. Join us and enhance your skill set to tackle complex data challenges with confidence!

00:00 Introduction
02:34 Concepts of Linear Algebra
10:26 Linear System of Equations
16:38 Matrix and it's operations
29:49 Vectors and its properties

✅Is linear algebra used in data science?
Matrix operations form the cornerstone of linear algebra, providing essential tools for manipulating and analyzing data in machine learning. In this section, we explore key matrix operations, including multiplication, transpose, inverse, and determinant, along with their significance and applications.

✅What linear algebra is needed for machine learning?
Linear algebra is the math behind machine learning. It lets you represent data, perform key operations on it, and understand complex algorithms like neural networks. Basically, it's the language machines use to learn from data.

✅What maths is required for data science and machine learning?
The core math for data science and machine learning involves three main areas:

Linear Algebra: This underpins data manipulation, algorithm implementation, and understanding complex models.
Statistics: It's essential for analyzing data, drawing inferences, and building effective models.
Calculus: It helps optimize machine learning algorithms and understand their behavior.

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➡️ About Artificial Intelligence Engineer

This Artificial Intelligence Engineer course Created in partnership with IBM, this course introduces students to blended learning and prepares them to be AI and Data Science specialists. In Armonk, New York, IBM is a significant cognitive service and integrated cloud solution firm that provides many technology and consulting solutions.

IBM is a leader in AI and Machine Learning technology verticals for 2021. This AI masters course will prepare students for Artificial Intelligence and Data Analytics careers.

✅ Key Features

- Add the IBM Advantage to your Learning
- 25 Industry-relevant Projects and Integrated labs
- Immersive Learning Experience
- Simplilearn's JobAssist helps you get noticed by top hiring companies

✅ Skills Covered

- ChatGPT
- Flask
- Matplotlib
- django
- Python
- Numpy
- Pandas
- SciPy
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- OpenCV
- And Many More…

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We will understand what is data science by looking at simple restaurant business example. Data science is a process of getting insights from data. You don't have to be deep learning expert in order to do data science, you can do that in plain old microsoft excel also (if dataset is small enough). In recent years volume of data has grown too much so that data has become BIG DATA. Microsoft excel can't work with big data hence you need tools such as,

#DataScience #WhatIsDataScience #DataScienceForBeginners #DataScientist #DataScienceTutorial #DataScienceWithPython #DataScienceCourse

1) Apache hadoop and apache spark: For database storage and distributed computing
2) Python and R: For data science programming
3) Tableau, Power BI, Matplotlib, MATLAB, Jupyter Notebook: For data visualization
4) Sklearn, Deep Learning, Tensorflow, PyTorch: For deep learning and machine learning

Data scientist has become the most popular job in the market today and there is a huge career scope if you know how to do data science. Some of the use cases of data science in real life are,

1) Healthcare: Diagnostic prediction and accuracy
2) Finance: Fraud detection, predictive analysis on loans, stock market movement, company future
3) Shipping: Figure out best route for shipping
4) E-commerce: Product recommendation, inventory pricing

Very Simple Explanation Of Neural Network: https://www.youtube.com/watch?v=ER2It2mIagI

Form to fill out your definition of data science (Fill free yo use innovative, poetic, funny language) https://forms.gle/ukkQKddkiwna1H1L7

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This Data Science tutorial will help you in understanding what is Data Science, why we need Data Science, the prerequisites for learning Data Science, what a Data Scientist does, the Data Science lifecycle with an example, and career opportunities in the Data Science domain. You will also learn the differences between Data Science and Business intelligence. The role of a data scientist is one of the sexiest jobs of the century. Every day, companies are looking out for more and more skilled data scientists and studies show that there is expected to be a continued shortfall in qualified candidates to fill the roles. So, let us dive deep into Data Science and understand what is Data Science all about.


This Data Science tutorial for beginners will cover the following topics:
Start (0:00)
1. Need for Data Science? ( 00:50 )
2. What is Data Science? ( 05:55 )
3. Data Science vs Business intelligence ( 11:44 )
4. Prerequisites for learning Data Science ( 16:36 )
5. What does a Data scientist do? ( 24:31 )
6. Data Science life cycle with use case ( 30:17 )
7. Demand for Data scientists ( 47:17 )

To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/S....implilearn?sub_confi

📚Data Science Article: https://bit.ly/30cYbpI

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➡️ About Data Science Course in collaboration with IBM

This Data Science course in collaboration with IBM propels your career to become a data scientist. Gain expertise in in-demand skills like Python, SQL, Excel, Machine Learning, Tableau, generative AI, and more. Dive deep into data interpretation nuances, master Machine Learning, and enhance programming skills to elevate your Data Science career.

Key Features
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Masterclasses from IBM experts
✅ Dedicated live sessions by faculty of industry experts
✅ Industry-recognized Data Scientist Master’s certificate from Simplilearn
✅ Industry-recognized IBM certifications for IBM courses
✅ Ask-Me-Anything (AMA) sessions with IBM leadership
✅ Capstone from 3 domains and 25+ projects
✅ Exclusive hackathons conducted by IBM
✅ Lifetime access to self-paced learning content
✅ Program crafted to initiate your journey as a Data Scientist
✅ Integrated labs for hands-on learning experience

Skills Covered
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Explainable AI
✅ Conversational AI
✅ Large Language Models
✅ Model Building and Finetuning
✅ Ensemble Learning
✅ Data Visualization
✅ Database Management

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Want to become a Data Scientist? 📊 In this short, we’ll break down the essential skills you need! From mastering data analysis and visualization to building machine learning models and using tools like Python, SQL, and R, these skills are crucial for transforming data into actionable insights. Whether you're a beginner or looking to refine your skills, this guide highlights the core competencies every Data Scientist should know. Don’t forget to follow for more data science tips and tutorials! 🔍

Want to become a Data Scientist by 2026?

Here’s your roadmap to success! This short video will guide you through the essential skills, tools, and technologies you need to master, including:

Python: Learn the key programming language for Data Science and Machine Learning.

Machine Learning: Understand how to build and apply models to solve real-world problems.

AI: Explore Artificial Intelligence and its role in data science and automation.

Cloud Analytics: Dive into the growing field of cloud-based data analytics tools and technologies.

Fast Career Path: Discover the quickest and most effective route to a data-driven career.

Stay updated with #simplilearn for more quick guides on mastering Data Science and building your future in tech!

#Coding #DataScience #Python #MachineLearning #AI #CloudAnalytics #TechCareers #DataScientist #FutureInTech #Shorts

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Statistics is a branch of applied mathematics, that is the study and manipulation of data, including ways to gather, review, analyze, and draw conclusions. This is why statistics still holds a very important place in today’s data science and business intelligence world. In this statistics tutorial, you will learn all about statistics, including, percentile in statistics, what is normal distribution, Central Limit Theorem, and probability density function. Start learning the statistics tutorial now.

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➡️ About Data Science Course in collaboration with IBM

This Data Science course in collaboration with IBM propels your career to become a data scientist. Gain expertise in in-demand skills like Python, SQL, Excel, Machine Learning, Tableau, generative AI, and more. Dive deep into data interpretation nuances, master Machine Learning, and enhance programming skills to elevate your Data Science career.

Key Features
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Masterclasses from IBM experts
✅ Dedicated live sessions by faculty of industry experts
✅ Industry-recognized Data Scientist Master’s certificate from Simplilearn
✅ Industry-recognized IBM certifications for IBM courses
✅ Ask-Me-Anything (AMA) sessions with IBM leadership
✅ Capstone from 3 domains and 25+ projects
✅ Exclusive hackathons conducted by IBM
✅ Lifetime access to self-paced learning content
✅ Program crafted to initiate your journey as a Data Scientist
✅ Integrated labs for hands-on learning experience

Skills Covered
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Explainable AI
✅ Conversational AI
✅ Large Language Models
✅ Model Building and Finetuning
✅ Ensemble Learning
✅ Data Visualization
✅ Database Management

👉 Learn More At: https://www.simplilearn.com/iitk-professional-certificate-course-data-analytics?utm_campaign=StatisticsForDataScience&utm_medium=Description&utm_source=youtube

🔥🔥

Check out Simplilearn (Generative AI and Machine Learning program): https://bit.ly/Genai-ml-program

In this video, I will tell you the complete Data Scientist roadmap - a step-by-step guide, from beginner to advanced. You’ll learn everything you need to become a successful data scientist, even if you’re starting from zero.

I’ll explain how AI is changing the tech industry, which jobs are getting replaced, and why data science is still one of the most powerful and in-demand careers in 2026. I'll go through all the essential skills: Mathematics, Python Programming, Machine Learning, Deep Learning, MLOps, and Generative AI, along with the best free resources to learn them & also show you how to build your portfolio, create real-world projects, and use tools like ChatGPT, Gemini, and Claude to become a 10x data scientist.

If you’re a student, IT professional, or software engineer planning to switch into AI, ML, or data science, this video is your complete guide. Watch the complete video to learn more, and also share it with your friends.

Many people are searching for:
- How to become a Data Scientist after class 12th?
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-- X, Formerly Twitter: https://x.com/nishantchahar11
‒ LinkedIn: https://in.linkedin.com/in/chaharnishant11
‒ Telegram Channel: https://t.me/chahar_nishant

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✅ Products I use: 💻📷
Green Soul Vision Gaming Chair: https://amzn.to/3g0yT5K
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Smartphone: https://amzn.to/30Kv0tP
Old Laptop: https://amzn.to/3j0hP0a
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Learn how I escaped the 9-5 through freelancing: https://learn.stfnvic.com/mastermind

🔗 MY FREE RESOURCES FOR YOU:
🌴 Join 2000+ people escaping the 9-5 and creating their dream life → https://www.skool.com/9-5-to-dream-life
📜 Get my "Master Plan Template" I used to escape the 9-5 and create my dream life →https://stefanovic92.gumroad.com/l/masterplan
✉️ Get my tips, tools & lessons in my 1-minute-freedom newsletter: →https://stfnvic.com

TOOLS THAT CHANGED MY LIFE:
📊 Save 25% off Datacamp: https://datacamp.pxf.io/WqWWXA
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Follow me here:
https://instagram.com/stefanovic92
https://www.twitter.com/stfnvic
https://www.linkedin.com/in/stefanmasnikovic/

What is Exploratory Data Analysis: https://ibm.biz/Exploratory_Data_Analysis

Create Data Fabric instead of data silos: https://ibm.biz/EDA_Data_Fabric

Exploratory data analysis (EDA) is used by data scientists to analyze and investigate data sets and summarize their main characteristics, often employing data visualization methods. IBM Master Inventor Martin Keen explains how it helps determine how best to manipulate data sources to get the answers you need, making it easier for data scientists to discover patterns, spot anomalies, test a hypothesis, or check assumptions.

Get started for free on IBM Cloud → https://ibm.biz/sign-up-now

Subscribe to see more videos like this in the future → http://ibm.biz/subscribe-now

#AI #Software #ITModernization #ExploratoryDataAnalysis #lightboard #IBM #DataFabric

Learn Machine Learning in a way that is accessible to absolute beginners. You will learn the basics of Machine Learning and how to use TensorFlow to implement many different concepts.

✏️ Kylie Ying developed this course. Check out her channel: https://www.youtube.com/c/YCubed

⭐️ Code and Resources ⭐️
🔗 Supervised learning (classification/MAGIC): https://colab.research.google.....com/drive/16w3TDn_tA
🔗 Supervised learning (regression/bikes): https://colab.research.google.....com/drive/1m3oQ9b0oY
🔗 Unsupervised learning (seeds): https://colab.research.google.....com/drive/1zw_6ZnFPC
🔗 Dataets (add a note that for the bikes dataset, they may have to open the downloaded csv file and remove special characters)
🔗 MAGIC dataset: https://archive.ics.uci.edu/ml..../datasets/MAGIC+Gamm
🔗 Bikes dataset: https://archive.ics.uci.edu/ml..../datasets/Seoul+Bike
🔗 Seeds/wheat dataset: https://archive.ics.uci.edu/ml/datasets/seeds

🏗 Google provided a grant to make this course possible.

❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp

⭐️ Contents ⭐️
⌨️ (0:00:00) Intro
⌨️ (0:00:58) Data/Colab Intro
⌨️ (0:08:45) Intro to Machine Learning
⌨️ (0:12:26) Features
⌨️ (0:17:23) Classification/Regression
⌨️ (0:19:57) Training Model
⌨️ (0:30:57) Preparing Data
⌨️ (0:44:43) K-Nearest Neighbors
⌨️ (0:52:42) KNN Implementation
⌨️ (1:08:43) Naive Bayes
⌨️ (1:17:30) Naive Bayes Implementation
⌨️ (1:19:22) Logistic Regression
⌨️ (1:27:56) Log Regression Implementation
⌨️ (1:29:13) Support Vector Machine
⌨️ (1:37:54) SVM Implementation
⌨️ (1:39:44) Neural Networks
⌨️ (1:47:57) Tensorflow
⌨️ (1:49:50) Classification NN using Tensorflow
⌨️ (2:10:12) Linear Regression
⌨️ (2:34:54) Lin Regression Implementation
⌨️ (2:57:44) Lin Regression using a Neuron
⌨️ (3:00:15) Regression NN using Tensorflow
⌨️ (3:13:13) K-Means Clustering
⌨️ (3:23:46) Principal Component Analysis
⌨️ (3:33:54) K-Means and PCA Implementations

🎉 Thanks to our Champion and Sponsor supporters:
👾 Raymond Odero
👾 Agustín Kussrow
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--

Learn to code for free and get a developer job: https://www.freecodecamp.org

Read hundreds of articles on programming: https://freecodecamp.org/news

In this video we will learn the Complete Data Science RoadMap. Detailed explanation from basics to advanced in Data Science and Step by Step RoadMap.
- How to start with Data Science
- Resources & Skills Required
- Basics to Advanced Data Scientist

We are also sharing the 👇
🚀 Data Science Complete Syllabus : https://www.apnacollege.in/course/prime-ai

Checkout Simplilearn's Data Analytics Course: https://bit.ly/codewithharry-simplilearn
Update: I have recently created a comprehensive course on AI-Powered Data Analytics covering Excel, Python, AI assisted advanced coding, AI assited web development, PowerBI, Tableau, SQL & much more. This course is modern, job-ready, and designed to the point.
Enroll here: https://www.codewithharry.com/....courses/the-ultimate



Download the Roadmap PDF: https://cwh-full-next-space.fr....a1.cdn.digitaloceans


►Checkout my English channel here: https://www.youtube.com/channe....l/UC7btqG2Ww0_2LwuQx
►Instagram: https://www.instagram.com/codewithharry

python, C, C++, Java, JavaScript and Other Cheatsheets [++]:
Playlist: https://www.youtube.com/playli....st?list=PLu0W_9lII9a

►Learn in One Video[++]:
Python Course with 5 Projects: https://www.youtube.com/watch?v=fqF9M92jzUo
Python[15 Hr]: https://www.youtube.com/watch?v=gfDE2a7MKjA&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Python Advance[3.5 Hr]: https://www.youtube.com/watch?v=61a7UkDO50s&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Python[1 Hr]: https://www.youtube.com/watch?v=qHJjMvHLJdg&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Python[2 Hr]: https://www.youtube.com/watch?v=ihk_Xglr164&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Python[15 Min]:https://www.youtube.com/watch?v=fr1f84rg4Nw&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
JavaScript[1 Hr]: https://www.youtube.com/watch?v=onbBV0uFVpo&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
C[1.3 Hr]-https://www.youtube.com/watch?v=YXcgD8hRHYY&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
php[1 Hr]: https://www.youtube.com/watch?v=xW7ro3lwaCI&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
php[2.3 Hr]:https://www.youtube.com/watch?v=1SnPKhCdlsU&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
php[Project]- https://www.youtube.com/watch?v=-al2bECumKg&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
HTML[30 Min]:https://www.youtube.com/watch?v=E3ByCRqE7Lo&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
CSS[8.5 Hr]:https://www.youtube.com/watch?v=Edsxf_NBFrw&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
CSS[1.4 Hr]:https://www.youtube.com/watch?v=u5-K_ua9sOw&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Wordpress[3.2 Hr]:https://www.youtube.com/watch?v=GlLRYml8mCY&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Angular[2 Hr]:https://www.youtube.com/watch?v=0LhBvp8qpro&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Java[2.3 Hr]:https://www.youtube.com/watch?v=rV_3Lewxx6o&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Web Scraping[1 Hr]:https://www.youtube.com/watch?v=uufDGjTuq34&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
MongoDB[2 Hr]:https://www.youtube.com/watch?v=oSIv-E60NiU&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Numpy[1 Hr]:https://www.youtube.com/watch?v=Rbh1rieb3zc&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Android Dev[12 Hr]- https://www.youtube.com/watch?v=mXjZQX3UzOs
Linux[1 Hr]:https://www.youtube.com/watch?v=_tCY-c-sPZc&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
JQuery[1.1 Hr]:https://www.youtube.com/watch?v=YFlx1C8XwR0&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Git and GitHub[1.1 Hr]:https://www.youtube.com/watch?v=gwWKnnCMQ5c&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7

►Complete course [playlist]:
React: https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Python-https://www.youtube.com/playli....st?list=PLu0W_9lII9a
OOP Python-https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Java:https://www.youtube.com/playli....st?list=PLu0W_9lII9a
JavaScript- https://www.youtube.com/playli....st?list=PLu0W_9lII9a
PHP-https://www.youtube.com/playli....st?list=PLu0W_9lII9a
C-https://www.youtube.com/playli....st?list=PLu0W_9lII9a
C++-https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Git & GitHub-https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Android Dev- https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Python GUI- https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Web Development- https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Python Django:https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Projects Using HTML, CSS & Javascript- https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Data Structure and Algo:https://www.youtube.com/playli....st?list=PLu0W_9lII9a

Follow Me On Social Media
►Website (created using Django Rest & Angular): https://www.codewithharry.com
►Facebook: https://www.facebook.com/CodeWithHarry
►Instagram: https://www.instagram.com/codewithharry/
Twitter: https://twitter.com/CodeWithHarry
Comment "#HarryBhai" if you read this 😉😉

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This Machine Learning basics video will help you understand what Machine Learning is, what are the types of Machine Learning - supervised, unsupervised & reinforcement learning, how Machine Learning works with simple examples, and will also explain how Machine Learning is being used in various industries. Machine learning is a core sub-area of artificial intelligence; it enables computers to get into self-learning mode without being explicitly programmed. When exposed to new data, these computer programs are enabled to learn, grow, change, and develop by themselves. So, the iterative aspect of machine learning is the ability to adapt to new data independently. This is possible as programs learn from previous computations and use “pattern recognition” to produce reliable results.

The below topics are explained in this Machine Learning basics video:
1. What is Machine Learning? ( 00:21 )
2. Types of Machine Learning ( 02:43 )
2. What is Supervised Learning? ( 02:53 )
3. What is Unsupervised Learning? ( 03:46 )
4. What is Reinforcement Learning? ( 04:37 )
5. Machine Learning applications ( 06:25 )

Subscribe to our channel for more Machine Learning Tutorials: https://www.youtube.com/user/S....implilearn?sub_confi

Download the Machine Learning Career Guide to explore and step into the exciting world of Machine Learning and follow the path toward your dream career- https://bit.ly/3eLuTUo

Watch more videos on Machine Learning: https://www.youtube.com/watch?v=7JhjINPwfYQ&list=PLEiEAq2VkUULYYgj13YHUWmRePqiu8Ddy

#MachineLearning #WhatIsMachineLearning #MachineLearningTutorial #MachineLearningBasics #MachineLearningTutorialForBeginners #Simplilearn

➡️ About Artificial Intelligence Engineer

This Artificial Intelligence Engineer course Created in partnership with IBM, this course introduces students to blended learning and prepares them to be AI and Data Science specialists. In Armonk, New York, IBM is a significant cognitive service and integrated cloud solution firm that provides many technology and consulting solutions.
IBM is a leader in AI and Machine Learning technology verticals for 2021. This AI masters course will prepare students for Artificial Intelligence and Data Analytics careers.

✅ Key Features
- Add the IBM Advantage to your Learning
- 25 Industry-relevant Projects and Integrated labs
- Immersive Learning Experience
- Simplilearn's JobAssist helps you get noticed by top hiring companies

✅ Tools Covered
- ChatGPT
- Flask
- Matplotlib
- django
- Python
- Numpy
- Pandas
- SciPy
- Keras
- OpenCV
- And Many More…

👉Learn More at: https://www.simplilearn.com/professional-aiml-program?utm_campaign=MachineLearningscribe&utm_medium=DescriptionFirstFold&utm_source=youtube

🔥PGP in Generative AI and ML in collaboration with Illinois Tech: https://www.edureka.co/executi....ve-programs/pgp-gene
🔥Generative AI Course: Master's Program: https://www.edureka.co/masters....-program/generative-

This Edureka video on *Artificial Intelligence Full Course* will provide you with a comprehensive and detailed knowledge of Artificial Intelligence concepts with hands-on examples. The following topics are covered in this Artificial Intelligence Full Course:

00:00 Introduction to Artificial Intelligence Course
02:27 History Of AI
06:45 Demand For AI
08:46 What Is Artificial Intelligence?
09:50 AI Applications
16:49 Types Of AI
20:24 Programming Languages For AI
27:12 Introduction To Machine Learning
28:08 Need For Machine Learning
31:48 What Is Machine Learning?
34:13 Machine Learning Definitions
37:26 Machine Learning Process
49:13 Types Of Machine Learning
49:21 Supervised Learning
52:00 Unsupervised Learning
53:44 Reinforcement Learning
55:29 Supervised vs Unsupervised vs Reinforcement Learning
58:23 Types Of Problems Solved Using Machine Learning
1:04:49 Supervised Learning Algorithms
1:05:17 Linear Regression
1:11:20 Linear Regression Demo
1:26:36 Logistic Regression
1:35:36 Decision Tree
1:55:18 Random Forest
2:07:31 Naive Bayes
2:14:37 K Nearest Neighbour (KNN)
2:20:31 Support Vector Machine (SVM)
2:26:40 Demo (Classification Algorithms)
2:42:36 Unsupervised Learning Algorithms
2:42:45 K-means Clustering
2:50:49 Demo (Unsupervised Learning)
2:56:40 Reinforcement Learning
3:24:36 Demo (Reinforcement Learning)
3:31:41 AI vs Machine Learning vs Deep Learning
3:33:08 Limitations Of Machine Learning
3:36:32 Introduction To Deep Learning
3:38:36 How Deep Learning Works?
3:40:48 What Is Deep Learning?
3:41:50 Deep Learning Use Case
3:43:14 Single Layer Perceptron
3:50:56 Multi Layer Perceptron (ANN)
3:52:55 Backpropagation
3:54:39 Training A Neural Network
4:01:02 Limitations Of Feed Forward Network
4:03:18 Recurrent Neural Networks
4:05:36 Convolutional Neural Networks
4:09:00 Demo (Deep Learning)
4:29:02 Natural Language Processing
4:30:53 What Is Text Mining?
4:32:43 What Is NLP?
4:33:26 Applications Of NLP
4:35:53 Terminologies In NLP
4:41:19 NLP Demo
4:47:21 Machine Learning Masters Program

📢📢 Check out the latest 2025 video on Top 10 Technologies for the most up-to-date insights!
📌 Top 10 Technologies to Learn in 2025 → https://youtu.be/5kjWh8lBxC4

🔴 𝐋𝐞𝐚𝐫𝐧 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐅𝐨𝐫 𝐅𝐫𝐞𝐞! 𝐒𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐭𝐨 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐘𝐨𝐮𝐓𝐮𝐛𝐞 𝐂𝐡𝐚𝐧𝐧𝐞𝐥: https://edrk.in/DKQQ4Py

Python Full Course: https://www.youtube.com/watch?v=WGJJIrtnfpk
Statistics and Probability Tutorial: https://www.youtube.com/watch?v=XcLO4f1i4Yo

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐏𝐲𝐭𝐡𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠𝐬

🔵 Python Programming Certification: http://bit.ly/37rEsnA
🔵 Python Certification Training for Data Science: http://bit.ly/2Gj6fux

🔴. 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐌𝐚𝐬𝐭𝐞𝐫𝐬 𝐏𝐫𝐨𝐠𝐫𝐚𝐦

🔵 Data Scientist Masters Program: http://bit.ly/2t1snGM
🔵 Machine Learning Engineer Masters Program: https://bit.ly/3Hi1sXN

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐏𝐫𝐨𝐠𝐫𝐚𝐦

🔵 Advanced Certificate Program in Data Science with E&ICT Academy, IIT Guwahati: http://bit.ly/3V7ffrh

🔵 University of Cambridge Online Certifications: https://bit.ly/3RSNTXi

Check out the entire Machine Learning Playlist: https://bit.ly/2NG9tK4
Check out the entire Machine Learning Blog list: https://bit.ly/2V2MnDW

#edureka #artificialIntelligence #artificialIntelligenceTutorial #artificialIntelligenceFullCourse #artificialIntelligenceEngineer

📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
📌𝐓𝐰𝐢𝐭𝐭𝐞𝐫: https://twitter.com/edurekain
📌𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧: https://www.linkedin.com/company/edureka
📌𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦: https://www.instagram.com/edureka_learning/
📌𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤: https://www.facebook.com/edurekaIN/
📌𝐒𝐥𝐢𝐝𝐞𝐒𝐡𝐚𝐫𝐞: https://www.slideshare.net/EdurekaIN
📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/

-------------------------------------

About the Masters Program

Edureka’s Machine Learning Engineer Masters Program makes you proficient in techniques like Supervised Learning, Unsupervised Learning and Natural Language Processing. It includes training on the latest advancements and technical approaches in Artificial Intelligence & Machine Learning such as Deep Learning, Graphical Models and Reinforcement Learning.

The Master's Program Covers Topics LIke:
Python Programming
PySpark
HDFS
Spark SQL
Machine Learning Techniques and Artificial Intelligence Types
Tokenization
Named Entity Recognition
Lemmatization
Supervised Algorithms
Unsupervised Algorithms
Tensor Flow
Deep learning
Keras
Neural Networks
Bayesian and Markov’s Models
Inference
Decision Making
Bandit Algorithms
Bellman Equation
Policy Gradient Methods.

-------------
For more information, please write back to us at sales@edureka.in or call us at IND: 9606058406 / US & RoW: +1-8335643323 (toll-free)

Kickstart your career in a Data Analyst. Apply today! - https://www.theiscale.com/Data....Analytics/data-analy

❇️ Explore our Job Oriented Courses: https://www.theiscale.com/explore-course
➖➖➖➖➖➖
📱 For Any Further Query or Doubts? Contact- 7880-113-112 (Student Helpline Number)
For any query connect in WhatsApp with us: https://wa.me/917880113112
➖➖➖➖➖➖
✳️ Join Telegram Channel- https://t.me/TheiScale
✳️ Join WhatsApp Channel- https://whatsapp.com/channel/0....029VaB5ekEKQuJQV572v
➖➖➖➖➖➖
✳️ For Notes & Study Material of Python 30 Days Class kindly Install our Android App- https://play.google.com/store/apps/details?id=com.logixhunt.ihhpet&pli=1
➖➖➖➖➖➖
💥 Detailed Syllabus of Python 30 Days YouTube Live Master Class- https://drive.google.com/file/....d/1RcfsKH1E63e9W1J6L
➖➖➖➖➖➖
💢 For Any Further Query or Doubts? Contact- 7880-113-112
🔥WhatsApp to Chat: https://wa.me/917880113112
🔥Join WhatsApp Channel for Job Updates: https://whatsapp.com/channel/0....029VaB5ekEKQuJQV572v
➖➖➖➖➖➖
➖➖➖➖➖➖
Python Programming Schedule for Day 01
🗓️ 13th April 2023 (Thursday)
⏰ 04:00 PM Onwards
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Hi Students, The iScale @theiScale organizing a Free 30 Days Live Master Class of Python Programming, in which we will teach Python from Basic to Advance Level. We will also discuss END TO END PROJECT in Python which will definitely help you to build a Strong Portfolio. This LIVE Master Class will gives you a better opportunities to learn and implement new things in Python Programming which makes you industry ready and grab a good salary package as fresher's as Data Analyst and also help to switch to higher salary packages if you are having experienced.
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**************************
#️⃣ Social Medias #️⃣
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You can start Placement Preparation with me in Alpha Plus
🔥Alpha Plus Placement Batch (Java+DSA) : https://www.apnacollege.in/course/alpha-plus
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Download Resources for Data Science : https://drive.google.com/drive..../folders/1wfNTKinBAV
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Program Details of Alpha PLUS
- Classes starting from 17th September
- Language : Java
- Complete Data Structures and Algorithms
- Beginners to Advanced
- 4 months duration
- Lectures on alternate days
- 300+ Question Practice
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- Library Feature
- Live sessions on Off-Campus Placement, Resume Preparation, Contest etc
- Live + VOD (video on demand) Batch

In this video, you will learn Machine Learning from Beginner to Advanced level step by step.

⬇️ Download the Full Machine Learning Notes here: https://www.theiscale.com/Data....Analytics/machine-le

This complete Machine Learning course is designed for:
✔ Beginners with no prior experience
✔ College students & freshers
✔ Data Science & AI aspirants
✔ Working professionals

📌 What you’ll learn in this course:
• Introduction to Machine Learning with AI
• Types of Machine Learning (Supervised, Unsupervised, Reinforcement)
• Linear & Logistic Regression
• Decision Trees & Random Forest
• KNN, Naive Bayes, SVM
• Clustering (K-Means, Hierarchical)
• Feature Engineering & Data Preprocessing
• Model Evaluation & Optimization
• Real-world Machine Learning Projects
• Career roadmap for ML & Data Science

Timestamp
00:00:00 -Course Introduction
00:03:24 -Technological Evolution: Web to Apps to ML
00:06:50 -Mapping the AI Branch: ML vs. Deep Learning vs. Data Science
00:13:33 -Dynamic Pricing Models and Negotiation Algorithms
00:15:45 -Chatbots and Virtual Assistants
00:16:01 -Sentiment Analysis, Customer Reviews
00:17:21 -The Machine Learning Model Workflow
00:17:44 -Data Pre-processing and Missing Values
00:18:20 -Model Training and Iterative Evaluation
00:19:19 -The Pillars of ML: Math, Coding, and Implementation
00:20:53 -Supervised, Unsupervised, and Reinforcement
00:21:37 - Reinforcement Learning: Agents, Environments, and Rewards
00:23:02 -Supervised Learning
00:25:37 -Regression Problems
00:27:27 -Classification Problems
00:28:10 - Loan Approval and Email Spam Categorization
00:28:47 - Dependent vs. Independent Features
00:32:00 - Binary vs. Multi-class Classification
00:34:18 - Unsupervised Learning
00:35:54 - Clustering and Pattern Recognition
00:39:57 - Dimensionality Reduction Explained
00:42:01 -Linear Regression Algorithm
00:43:00 - Introduction to Linear Regression
00:45:08 - The Concept of the Best Fit Line
00:48:10 - ML Notation
00:49:07 - Intercepts and Slopes Defined
00:51:59 - Defining the Cost Function
00:53:53 - Error Minimization Strategy
00:57:48 - Gradient Descent Logic and Global Minima
01:04:23 - Practical: Setting up Anaconda and Jupyter Notebook
01:06:55 - Practical: Housing Price Prediction Coding
01:08:14 - Importing NumPy, Pandas, and Matplotlib
01:14:09 - Dividing Data into X and Y Features
01:19:50 - Implementing Cross-Validation Scores
01:34:16 - Interpreting Final Accuracy Results
01:34:17 - Ridge & Lasso Algorithm
01:35:42 - Overfitting and Underfitting
01:37:04 - Bias vs.Variance Trade-off
01:39:56 -Ridge Regression
01:41:05 -Handling Multi-Collinearity
01:43:42 -Lasso Regression
01:46:30 -Feature Selection via Lasso
01:52:12 -Grid Search CV Implementation
01:58:12 -Standard Scaling of Features
01:59:10: Logistic Regression Algorithm
02:04:43 -Introduction to Logistic Regression
02:07:06 -Sigmoid Function Mathematics
02:07:54 -Linear Regression Line
02:08:13 -Decision Boundaries
02:09:57 -Logistic Regression Cost Function Issues
02:14:42 -The Confusion Matrix
02:16:40 -True Positives, False Positives, and Errors
02:18:32 -Precision, Recall, F1-Score
02:22:26 -Practical: Breast Cancer Prediction Implementation
02:41:21 -Visualizing the Confusion Matrix with Heatmaps
02:45:47-Naive Bayes Algorithm Fundamentals
02:46:18 -Dependent and Independent Events
02:50:50 -Bayes Theorem Formula Construction
02:54:01 -Gaussian Naive Bayes Implementation
03:08:47 -K-Nearest Neighbors (KNN) Theory
03:12:32 -Manhattan vs. Euclidean Distance
03:27:48 -Decision Tree Algorithm Structure
03:30:46 -Root Nodes, Leaf Nodes, and Pure Splits
03:35:16 -Entropy and Gini Impurity Calculations
03:44:01 -Information Gain and Feature Selection
03:55:05 -Practical: with Scikit-Learn
03:56:02 - Unsupervised Algorithms
04:13:45 -Ensemble Techniques: Bagging vs. Boosting
04:15:56 -Bootstrap Aggregating
04:18:38 -Random Forest Algorithm
04:33:45 -AdaBoost Algorithm
04:57:52 -K-Means Clustering Algorithm
05:00:30 -The Elbow Method for Optimal Clusters
05:11:14 -Hierarchical Clustering and Dendrograms
05:16:50 -DBScan: Density-Based Clustering
05:24:44 -Final Summary and Career Roadmap

⚙️ Tools & Libraries:
Python, NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn
👉 By the end of this course, you will be confident to build Machine Learning models from scratch.

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My Data Science Course: https://www.codewithharry.com/....courses/the-ultimate
Data Science Course (International Students): https://buy.stripe.com/8wMdSN4vibLjcU0bII
Data Science Course (International Option 2): https://codeharry.gumroad.com/l/ds
My Udemy Python Course(Coupon Applied): https://goharry.in/python
Try Quadratic: https://quadratic.ai/codewithharry

I use Quadratic AI across the entire data science life cycle, from accessing data, cleaning it, analyzing it with Python + Pandas, and visualizing it with Plotly and Chart.js.

Download the Roadmap PDF: https://cwh-full-next-space.fr....a1.cdn.digitaloceans
►Checkout my English channel here: https://www.youtube.com/channe....l/UC7btqG2Ww0_2LwuQx
►Instagram: https://www.instagram.com/codewithharry

python, C, C++, Java, JavaScript and Other Cheatsheets [++]:
Playlist: https://www.youtube.com/playli....st?list=PLu0W_9lII9a

►Learn in One Video[++]:
Python Course with 5 Projects: https://www.youtube.com/watch?v=fqF9M92jzUo
Python[15 Hr]: https://www.youtube.com/watch?v=gfDE2a7MKjA&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Python Advance[3.5 Hr]: https://www.youtube.com/watch?v=61a7UkDO50s&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Python[1 Hr]: https://www.youtube.com/watch?v=qHJjMvHLJdg&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Python[2 Hr]: https://www.youtube.com/watch?v=ihk_Xglr164&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Python[15 Min]:https://www.youtube.com/watch?v=fr1f84rg4Nw&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
JavaScript[1 Hr]: https://www.youtube.com/watch?v=onbBV0uFVpo&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
C[1.3 Hr]-https://www.youtube.com/watch?v=YXcgD8hRHYY&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
php[1 Hr]: https://www.youtube.com/watch?v=xW7ro3lwaCI&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
php[2.3 Hr]:https://www.youtube.com/watch?v=1SnPKhCdlsU&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
php[Project]- https://www.youtube.com/watch?v=-al2bECumKg&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
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CSS[1.4 Hr]:https://www.youtube.com/watch?v=u5-K_ua9sOw&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Wordpress[3.2 Hr]:https://www.youtube.com/watch?v=GlLRYml8mCY&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Angular[2 Hr]:https://www.youtube.com/watch?v=0LhBvp8qpro&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Java[2.3 Hr]:https://www.youtube.com/watch?v=rV_3Lewxx6o&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Web Scraping[1 Hr]:https://www.youtube.com/watch?v=uufDGjTuq34&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
MongoDB[2 Hr]:https://www.youtube.com/watch?v=oSIv-E60NiU&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Numpy[1 Hr]:https://www.youtube.com/watch?v=Rbh1rieb3zc&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Android Dev[12 Hr]- https://www.youtube.com/watch?v=mXjZQX3UzOs
Linux[1 Hr]:https://www.youtube.com/watch?v=_tCY-c-sPZc&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
JQuery[1.1 Hr]:https://www.youtube.com/watch?v=YFlx1C8XwR0&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7
Git and GitHub[1.1 Hr]:https://www.youtube.com/watch?v=gwWKnnCMQ5c&list=PLu0W_9lII9ahKZ42vg2w9ERPmShYbYAB7

►Complete course [playlist]:
React: https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Python-https://www.youtube.com/playli....st?list=PLu0W_9lII9a
OOP Python-https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Java:https://www.youtube.com/playli....st?list=PLu0W_9lII9a
JavaScript- https://www.youtube.com/playli....st?list=PLu0W_9lII9a
PHP-https://www.youtube.com/playli....st?list=PLu0W_9lII9a
C-https://www.youtube.com/playli....st?list=PLu0W_9lII9a
C++-https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Git & GitHub-https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Android Dev- https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Python GUI- https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Web Development- https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Python Django:https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Projects Using HTML, CSS & Javascript- https://www.youtube.com/playli....st?list=PLu0W_9lII9a
Data Structure and Algo:https://www.youtube.com/playli....st?list=PLu0W_9lII9a

Follow Me On Social Media
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Comment "#HarryBhai" if you read this 😉😉

Data Scientist Roadmap 2025 | How to Become a Data Scientist Step-by-Step

#HowToLearnDataScienceFastIn2025 #HowToLearnDataScience #HowToLearnDataScienceForFree
#HowToLearnDataScienceForBeginners #LearnDataScienceForFree #DataScienceRoadmap
#DataScienceRoadmap2025 #HowToBecomeADataScientist #Intellipaat #shorts

Want to know How to Learn Data Science Fast in 2025? Follow this video and discover the BEST Data Science Roadmap YOU MUST FOLLOW in 2025 to land a job. In this video, you will also discover the learning materials or courses from which you can learn the required skills. Whether you’re a beginner, a working professional, or someone looking to switch careers, this step-by-step guide will help you navigate your Data Science journey the right way.

💡 FAQs on Learning Data Science
❓ How to learn Data Science fast in 2025?
Follow a structured roadmap that includes Python, SQL, Machine Learning, Deep Learning, and real-world projects. Start with free courses, practice coding daily, and work on projects.

❓ How long does it take to become a Data Scientist?
If you learn consistently, it can take 6-12 months to become job-ready. The key is hands-on practice and real-world projects.

❓ Can I learn Data Science for free?
Yes! There are plenty of free resources. This video covers some of the best free Data Science courses available.

Build your first AI project with Python! 🤖 This beginner-friendly machine learning tutorial uses real-world data.

❤️ Join this channel to get access to perks:
https://www.youtube.com/channe....l/UCWv7vMbMWH4-V0ZXd

👍 Subscribe for more awesome Python tutorials like this: https://goo.gl/6PYaGF

👉 Get the CSV file: https://github.com/mosh-hameda....ni/python-supplement

💡 Need Python basics? Check out these resources:
- Python in 1 Hour: https://youtu.be/kqtD5dpn9C8
- Full Python Course: https://www.youtube.com/watch?v=_uQrJ0TkZlc

✋ Stay connected:
- Twitter: https://twitter.com/moshhamedani
- Facebook: https://www.facebook.com/programmingwithmosh/
- Instagram: https://www.instagram.com/codewithmosh.official/
- LinkedIn: https://www.linkedin.com/school/codewithmosh/

💡 What you'll learn:
- Foundational machine learning concepts.
- How to apply algorithms using Python.
- Work with real-world data for practical results.

👉 This tutorial is perfect for you if:
- You're curious about AI and machine learning.
- You have basic Python knowledge.
- You want a hands-on learning experience.

Let's get started!

📖 TABLE OF CONTENT
0:00:00 Introduction
0:00:59 What is Machine Learning?
0:02:58 Machine Learning in Action
0:05:45 Libraries and Tools
0:10:40 Importing a Data Set
0:17:01 Jupyter Shortcuts
0:22:53 A Real Machine Learning Problem
0:26:09 Preparing the Data
0:29:15 Learning and Predicting
0:33:20 Calculating the Accuracy
0:39:41 Persisting Models
0:42:55 Visualizing a Decision Tree

#Python #AI #MachineLearning

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Are you interested in data science? And have you heard of data analytics, but aren't sure how they're different? In this video, Martin Keen explains that while data science and data analytics are often used interchangeably, they have distinct roles. In terms of job roles, he covers the tools and practices of data scientists and contrast them with those of data analysts.

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The Statistics and Probability Full Course 2025 by Simplilearn, provides a comprehensive foundation for anyone entering the fields of data science, AI, or machine learning. It begins with the core principles of probability and statistics, ensuring learners grasp essential mathematical concepts needed for data-driven problem-solving. The course then bridges into mathematics for machine learning, followed by specialized sections on statistics for data science and probability for AI applications. Learners also explore the fundamentals and roadmap of data science, gaining clarity on how statistical methods power real-world analytics and predictive models. The program concludes with interview preparation, featuring top data science interview questions, helping learners confidently transition from theory to professional application.

Following are the topics covered in Probability and Statistics Full Course 2025:

00:00:00 - Introduction to Statistics and Probability Full Course 2025
00:02:07 - Probability and Statistics
00:48:26 - Mathematics for machine learning
02:38:50 - Statistics For Data Science
03:02:12 - Probability And Statistics For Data Science and AI
03:49:26 - What is Data Science
03:53:47 - Data science course unboxing
03:59:57 - Roadmap to Data Science
04:09:09 - Data Science Fundamentals
07:26:08 - Data Science Interview Questions and Answers

✅ Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

⏩ Check out the Data Science tutorial videos: https://www.youtube.com/watch?v=X3paOmcrTjQ&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6

#Probability #statistics #DataScience #artificialintelligence #ai #datascience #mathematics #MachineLearning #2025 #Simplilearn

✅ About Post Graduate Program In Data Science:
This in-depth Data Science program is designed for working professionals, and covers job-critical topics like R, Python programming, Machine Learning techniques, NLP notions, and Data Visualization with Tableau, using an active learning model that includes live sessions from global professionals, practical labs, IBM Hackathons, and corporate ready projects

Key Features
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✅ Core curriculum delivered in live online classes by industry experts
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✅ Engage in live online masterclasses led by Industry Expert, staff, and IBM experts
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✅ Gain exposure to ChatGPT, Gemini, Keras, TensorFlow and other prominent tools
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✅ 3 capstones and 25+ hands-on projects from various industry domains
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Skills Covered
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
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✅ Supervised and Unsupervised Learning
✅ Ensemble Learning
✅ Deep Learning
✅ Data Visualization
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✅ Explainable AI
✅ Machine Learning Algorithms
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
✅ Speech Recognition

Learning Path
✅ Program Induction
✅ Programming Refresher
✅ Data Management using SQL
✅ Python for Data Science (IBM)
✅ Applied Data Science with Python
✅ Machine Learning
✅ Deep Learning Specialization

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Join us for the AI & ML Full Course 2026, a complete live tutorial hosted by edureka! designed to help you master Artificial Intelligence and Machine Learning from the ground up. This live session will guide you through key concepts such as supervised and unsupervised learning, deep learning, neural networks, natural language processing, and real-world model deployment. Whether you're a beginner looking to enter the world of AI or a professional aiming to enhance your skills, this course is structured to make complex topics easy to understand. Using hands-on projects and Python-based examples, you’ll gain the practical knowledge needed to build intelligent systems and data-driven applications. This session is ideal for students, job seekers, developers, and tech enthusiasts who want to stay ahead in the AI/ML landscape in 2025. Make sure to join live to engage with instructors in real time and earn your certificate of participation. Subscribe to our channel and turn on notifications so you don’t miss this powerful learning experience.
00:00:00 Introduction
00:01:47 What is Artificial Intelligence?
00:07:49 Types of Artificial Intelligence
00:18:56 AI vs Machine Learning vs Deep Learning
00:32:41 Artificial Intelligence with Python
02:11:47 What is Machine Learning?
02:23:29 Types of Machine Learning Models
02:30:35 Machine Learning Algorithm
02:52:29 Linear Regression Algorithm
02:59:55 Logistic Regression Algorithm
03:47:04 Linear Regression Vs Logistic Regression
03:50:35 Decision Tree Algorithm
04:36:09 Random Forest
05:01:24 KNN Algorithm
05:33:47 Naive Bayes Classifier
05:55:28 Support Vector Machine
06:20:59 K- Means Clustering Algorithm
06:44:19 Hierarchical Clustering
06:50:41 Apriori Algorithm Explained
07:08:11 What is Deep Learning?
07:30:14 Artificial Neural Network
08:02:35 Convolutional Neural Network
08:23:06 Recurrent Neural Networks
08:52:02 LSTM Explained
09:45:59 Transformers Neural Networks Explained
09:56:02 What are GANs?
10:08:22 Future of AI/ML
10:22:58 Artificial Intelligence Interview Questions & Answers

🔴 𝐋𝐞𝐚𝐫𝐧 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐅𝐨𝐫 𝐅𝐫𝐞𝐞! 𝐒𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐭𝐨 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐘𝐨𝐮𝐓𝐮𝐛𝐞 𝐂𝐡𝐚𝐧𝐧𝐞𝐥: https://edrk.in/DKQQ4Py

📝Feel free to share your comments below.📝

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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Starting your data science journey?

Just dipping your toe into Machine Learning?

Not too sure how to get started with the wild world of Python?

I got you.

There’s a ton of stuff to learn when you’re just getting started with data science, but having a good foundation in Python will set you up for success. That being said there’s a lot of fluff that can derail you when you’re learning.

So I put this together.

This is everything I wish I would have learned when starting off my journey in Data Science. It’s all of the Python that I use in my day to day job and it’s more than enough to get you started!

In this video, you’ll learn:
1. How to setup your environment for Python
2. Fundamentals of coding with Python with a focus on Data Science Applications
3. Applications of Python for Data Science along with some practical Python projects

Link to Code: https://github.com/nicknochnac....k/PythonForDataScien

Link to Projects:
Project 1 - End to End Machine Learning: https://www.youtube.com/playli....st?list=PLgNJO2hghbm
Project 2 - Data Science Basics: https://www.youtube.com/playli....st?list=PLgNJO2hghbm
Project 3 - Deep Learning Summarization: https://youtu.be/TsfLm5iiYb4
Project 4 - Sentiment Analysis: https://youtu.be/szczpgOEdXs

Other projects
AI for Gaming: https://youtu.be/hCeJeq8U0lo
Object Detection: https://youtu.be/yqkISICHH-U

Chapters
0:00 - Start
1:16 - Why you should learn Python
6:08 - How to get started
6:59 - Installing Anaconda
11:42 - Starting Jupyter Notebooks
13:42 - Creating a Jupyter Notebook
16:10 - Jupyter Shortcuts
17:54 - Exporting Jupyter to .py
21:04 - Cell Types
23:16 - Working with Markdown
25:23 - Accessing Documentation
26:42 - Google Colab
28:40 - Watson Studio
33:23 - SECTION 2 Variables & Data Types
34:38 - CRUD
41:13 - Variables
47:18 - Data Types
49:09 - Strings
52:52 - Integers
54:55 - Floats
56:27 - Booleans
1:00:44 - Lists
1:05:28 - Tuples
1:12:43 - Sets
1:21:05 - Dictionaries
1:28:17 - CRUD for Lists
1:30:14 - Creating a List
1:31:33 - Reading a List Using Indexing
1:32:55 - Updating List Values
1:33:58 - Using .append()
1:34:57 - Using .insert()
1:39:21 - CRUD for Dictionaries
1:39:58 - Create a Dictionary
1:41:41 - Read from a Dictionary
1:42:46 - Accessing Dictionary .keys()
1:43:27 - Accessing Dictionary .values()
1:43:57 - Updating Dictionaries
1:46:50 - Deleting from a Dictionary
1:48:54 - SECTION 3 Conditions & Loops
1:52:23 - Conditions and Logic
1:54:47 - if Statement
2:02:54 - else Statement
2:05:28 - elif Statement
2:09:46 - in Statement
2:17:29 - for Loop
2:25:27 - continue, break, pass
2:32:32 - while Loop
2:39:59 - Looping through Dictionaries
2:48:28 - List comprehensions
2:52:00 - SECTION 4 Functions
2:55:59 - Defining Functions
3:02:36 - Positional Arguments
3:10:47 - Multiple Positional Arguments
3:15:34 - Looping with an Index
3:21:35 - Keyword Arguments
3:25:35 - Combining Positional and Keyword Args
3:32:11 - return Keyword
3:34:52 - lambda Functions
3:39:00 - SECTION 5 Classes
3:42:41 - Classes
3:44:52 - class Statement
3:45:45 - __init__ Method
3:47:01 - self keyword
3:49:02 - Assigning properties
3:49:34 - Creating an object
3:51:36 - Methods
4:03:03 - Class Inheritance
4:06:36 - Defining a Child Class
4:08:10 - Inheriting using the super() function
4:18:25 - SECTION 6 - Modules and Packages
4:21:45 - Modules
4:23:05 - Creating a helper module
4:25:42 - Importing modules
4:27:25 - Accessing Python Packages
4:29:00 - Working with APIs
4:32:02 - Installing packages with pip install
4:33:42 - Viewing installed packages with pip list
4:34:36 - Importing Packages
4:35:41 - Making API calls with requests.get()
4:45:46 - Parsing JSON
4:57:24 - SECTION 7 Files & Error handling
5:01:26 - Working with Files
5:02:32 - Writing Files using the with statement
5:07:04 - Reading from files
5:11:01 - Error Handling
5:14:26 - Using try except statements
5:19:37 - SECTION 8 Math and Projects
5:22:48 - Math in Python
5:24:54 - Math Operators
5:25:20 - Addition
5:26:01 - Subtraction
5:26:42 - Division
5:27:37 - Floor Division
5:29:06 - Modulus
5:31:28 - Multiplication
5:31:59 - Power
5:32:52 - Rounding with round()
5:34:15 - Absolute Values abs()
5:38:29 - Math Package
5:40:45 - Python Projects




Oh, and don't forget to connect with me!
LinkedIn: https://bit.ly/324Epgo
Facebook: https://bit.ly/3mB1sZD
GitHub: https://bit.ly/3mDJllD
Patreon: https://bit.ly/2OCn3UW
Join the Discussion on Discord: https://bit.ly/3dQiZsV

Happy coding!
Nick

P.s. Let me know how you go and drop a comment if you need a hand!

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02:08:01 - Data Visualization with Seaborn
02:56:12 - Exploratory Data Analysis (EDA)
03:35:30 - Types of Machine Learning
03:47:51 - Linear Regression
07:04:00 - Logistic Regression
07:44:27 - Support Vector Machine (SVM)
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00:04:21 - What is Data Science
00:13:33 - Roadmap to Data Science
05:23:46 - Data Science basics
06:10:05 - Probability and Statistics
09:28:02 - Reinforcement Learning
- Classification of Machine Learning
- AI Agents Tutorial
- Data Science Interview Questions

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⏩ Check out the Data Science tutorial videos: https://www.youtube.com/watch?v=X3paOmcrTjQ&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6

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Learning Path
✅ Program Induction
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Step into the world of Data Science with this complete Data Science Full Course 2025, designed for beginners as well as professionals looking to upskill. This in-depth course takes you from the very basics of data science to advanced concepts used by industry experts. You’ll start by understanding what data science really is and explore the key differences between Data Engineer, Data Scientist, and Data Analyst roles. The video then walks you through a clear data science roadmap, followed by hands-on learning with Python, Pandas, data visualization using Matplotlib, and Exploratory Data Analysis (EDA).

As you progress, you’ll dive into machine learning concepts, including Linear Regression, Logistic Regression, Support Vector Machines (SVM), Decision Trees, and K-Means Clustering. The course also includes a real-world data science project walkthrough to help you apply what you’ve learned. To help you prepare for jobs, the video covers data science interview questions and ends with a MCP Server tutorial for practical exposure.

If you’re aiming for a career in data science in 2025, this course is a must-watch.

➡️ Below are the topics covered in Data Science Full Course 2026:
00:00:00 – Introduction to Data Science Full Course 2025
00:01:37 – What is Data Science?
00:06:31 – Data Engineer vs Data Scientist vs Data Analyst
00:15:47 – Roadmap for Data Science
00:24:47 – Python for Data Science
00:27:28 – Pandas for Data Science
01:33:31 – Data Visualization with Matplotlib
02:23:55 – Exploratory Data Analysis (EDA)
03:02:53 – Machine Learning Types
03:14:19 – Linear Regression
06:31:23 – Logistic Regression
07:11:48 – Support Vector Machine (SVM)
07:13:31 – Decision Tree
07:16:01 – Clustering (K-Means)
08:11:18 – Data Science Project Walkthrough
09:31:53 – Data Science Interview Questions
10:37:08 – MCP Server Tutorial

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🔥Register for Intellipaat's Premium Data Science Course: https://intellipaat.com/data-s....cientist-course-trai

➡️ About Data Science Course:
This online Data Science course, in collaboration with iHUB, IIT Roorkee & Microsoft, will help you to elevate your Data Science career. In this course, you will master skills like Python, SQL, Statistics, Machine Learning, AI, Power BI & Generative AI, along with real-time industry-oriented projects.

➡️ Key Features:
✅ 50+ Live interactive sessions across 7 months
✅ 218 Hrs Self-paced Videos
✅ 50+ Industry relevant Projects & Quizzes
✅ Live Classes from IIT Faculty & Industry Experts
✅ Certification from iHub IIT Roorkee & Microsoft
✅ 2 Days Campus Immersion at iHub IIT Roorkee

➡️ What’s Covered in This Program?
✅ Linux and Python Fundamentals
✅ Data Wrangling with SQL
✅ Python with Data Science
✅ Linear Algebra and Advanced Statistics
✅ Machine Learning and Prediction Algorithms
✅ Supervised and Unsupervised Learning in ML
✅ Deep Learning with TensorFlow
✅ Generative AI & Prompt Engineering
✅ Deploying Machine Learning Models on Cloud
✅ Data Visualization Tool Power BI

📌 Do subscribe to Intellipaat channel & come across more relevant Tech content: https://goo.gl/hhsGWb

▶️ Intellipaat Achievers Channel: https://www.youtube.com/@intellipaatachievers

📚For more information, please write back to us at sales@intellipaat.com or call us at IND: +91-7022374614 / US : 1-800-216-8930

𝐄𝐝𝐮𝐫𝐞𝐤𝐚'𝐬 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐌𝐚𝐬𝐭𝐞𝐫𝐬 𝐩𝐫𝐨𝐠𝐫𝐚𝐦: https://www.edureka.co/masters....-program/data-scient
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00:00:00 Introduction
00:01:54 What is Data Science?
00:09:36 Who is a Data Scientist?
00:41:46 Top 10 Reasons to Learn Data Science
00:46:22 Data Science Basics
01:39:38 Data Life Cycle
01:43:13 Statistics and Probability
03:15:43 Hypothesis Testing Statistics
04:08:36 What is Machine Learning?
04:25:31 Linear Regression
04:52:09 Logistic Regression
05:40:38 Decision Tree Algorithm
06:26:00 Random Forest
06:53:11 KNN Algorithm
07:25:37 Naive Bayes Classifier
07:45:55 Support Vector Machine
08:11:23 K- Means Clustering Algorithm
08:31:32 Apriori Algorithm Explained
09:01:13 Reinforcement Learning
09:22:40 What is Deep Learning?
09:46:33 Introduction to Keras
10:18:01 Data Science Roadmap
10:27:15 Data Science vs Data Analytics
10:37:14 Data Science for Non Programmers
11:05:10 Data Science Interview Questions

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📝Feel free to share your comments below.📝

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This Python data science course will take you from knowing nothing about Python to coding and analyzing data with Python using tools like Pandas, NumPy, and Matplotlib.


💻 Code: https://github.com/datapublish....ings/Course-python-d

This is a hands-on course and you will practice everything you learn step-by-step. This course was created by Maxwell Armi. You can check out more of his data science videos on his YouTube channel here: https://www.youtube.com/c/AISciencesLearn

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⭐️ Course Contents ⭐️
⌨️ (0:00:00) Introduction to the Course and Outline
⌨️ (0:03:53) The Basics of Programming
⌨️ (1:11:35) Why Python
⌨️ (1:33:09) How to Install Anaconda and Python
⌨️ (1:37:25) How to Launch a Jupyter Notebook
⌨️ (1:46:28) How to Code in the iPython Shell
⌨️ (1:53:33) Variables and Operators in Python
⌨️ (2:27:45) Booleans and Comparisons in Python
⌨️ (2:55:37) Other Useful Python Functions
⌨️ (3:20:04) Control Flow in Python
⌨️ (5:11:52) Functions in Python
⌨️ (6:41:47) Modules in Python
⌨️ (7:30:04) Strings in Python
⌨️ (8:23:57) Other Important Python Data Structures: Lists, Tuples, Sets, and Dictionaries
⌨️ (9:36:10) The NumPy Python Data Science Library
⌨️ (11:04:12) The Pandas Python Data Science Python Library
⌨️ (12:01:31) The Matplotlib Python Data Science Library
⌨️ (12:09:00) Example Project: A COVID19 Trend Analysis Data Analysis Tool Built with Python Libraries

This Data Science Full Course for Beginners by Intellipaat is your all-in-one guide to mastering the core concepts, math, and practical tools used by professional data scientists. Begin with “What is Data Science?” and follow a step-by-step roadmap designed to help you become industry-ready. Understand the math behind Linear Regression, explore R-Squared metrics, and get hands-on with model implementation. Dive deep into essential algorithms like Logistic Regression, Support Vector Machines (SVM), Decision Trees, and K-Means Clustering with practical demos.

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00:00:00 – Introduction to Data Science Course
00:01:31 – What is Data Science?
00:06:22 – Data Scientist Roadmap
00:17:23 – Intro to Linear Regression
00:19:15 – Math Behind Linear Regression
01:08:36 – R-Squared Metrics
01:41:58 – Hands-on: Linear Regression
03:34:02 – Logistic Regression
03:36:06 – SVM Algorithm
03:37:26 – Decision Tree Algorithm
03:40:16 – K-Means Clustering Explained
05:33:19 – K-Means Hands-on
06:57:49 – Feature Engineering Techniques
07:07:16 – PCA (Principal Component Analysis)
10:14:30 – LDA (Linear Discriminant Analysis)
10:59:44 – Interview Questions (Data Science)

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✅ Linux and Python Fundamentals
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Learn the basic components of Data Science in this crash course for beginners.
If you want to learn more about data science after completing this course, check out Max's Free Getting Started with Data Science Workshop: https://codingwithmax.com/webinar/data-scientist/

In this course for beginners, you will learn about:

1. Statistics: we talk about the types of data you'll encounter, types of averages, variance, standard deviation, correlation, and more.

2. Data visualization: we talk about why we need to visualize our data, and the different ways of doing it (1 variable graphs, 2 variable graphs and 3 variable graphs.)

3. Programming: we talk about why programming helps us with data science including the ease of automation and recommended Python libraries for you to get started with data science.

❤️ Try interactive Databases courses we love, right in your browser: https://scrimba.com/freeCodeCamp-Databases (Made possible by a grant from our friends at Scrimba)

⭐️ Contents ⭐️
⌨️ (0:00:00) Introduction
⌨️ (0:10:52) Statistical Data Types
⌨️ (0:25:10) Types of Averages
⌨️ (0:38:55) Spread of Data
⌨️ (0:50:54) Quantiles and Percentiles
⌨️ (0:55:52) Importance of Data Visualization
⌨️ (1:05:14) One Variable Graphs
⌨️ (1:12:04) Two Variable Graphs
⌨️ (1:25:08) Three and Higher Variable Graphs
⌨️ (1:31:20) Programming

Course from Coding With Max. Check out the Coding With Max blog: https://www.codingwithmax.com/blog
Full data science course: https://codingwithmax.teachabl....e.com/p/data-scienti

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🏁 YouTube Video Chapters with Timestamps:
00:00 – Introduction
02:22 – Statistics vs Machine Learning
09:05 – Types of Statistics: Descriptive, Prescriptive, Predictive
01:50:45 – Types of Data
02:46:02 – Correlation
02:52:33 – Covariance
04:26:55 – Introduction to Probability
05:24:00 – Conditional Probability with Bayes’ Theorem
06:17:01 – Binomial Distribution
06:36:02 – Poisson Distribution

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#StatisticsForDataScience #ProbabilityAndStatistics #DataScienceForBeginners #LearnStatistics #DataScienceTutorial #MachineLearningBasics #GreatLearning

Mathematics and statistics for data science and machine learning: I am thrilled to announce that with this video I am starting a new series called mathematics and statistics for data science and machine learning. Math and stats as a field are very vast and whenever someone starts studying data science or machine learning the confusion is "how much math or statistics should I learn?" In this playlist I will cover only essential topics that can help you in your data science or ML journey.

Math/Stats for Data science, ML playlist: https://www.youtube.com/playli....st?list=PLeo1K3hjS3u
Math/Stats for Data science, ML playlist Hindi:https://www.youtube.com/playli....st?list=PLPbgcxheSpE

Check our Math and Statistics course for Data Science here : https://codebasics.io/courses/....math-and-statistics-

Do you want to learn technology from me? Check https://codebasics.io/?utm_source=description&utm_medium=yt&utm_campaign=description&utm_id=description for my affordable video courses.

🌎 Website: https://codebasics.io/?utm_source=description&utm_medium=yt&utm_campaign=description&utm_id=description

🎥 Codebasics Hindi channel: https://www.youtube.com/channe....l/UCTmFBhuhMibVoSfYo

#️⃣ Social Media #️⃣
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❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

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This Data Science Full Course 2026 by Simplilearn provides a structured learning path for mastering data science concepts. It starts with an introduction to data science, followed by a roadmap to becoming a data scientist. Learners will explore deep learning, probability, and statistics, which form the foundation of data science. The course then introduces Large Language Models (LLMs), benchmarking techniques, and the key differences between AI, ML, and DL. It also covers AI bias, OpenAI ChatGPT, and Generative AI tools for job interviews. Practical aspects are included with beginner-friendly machine learning projects and an overview of Mistral AI. Finally, the course concludes with data science interview questions, ensuring learners are well-prepared for real-world applications and job opportunities.

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00:04:21 - What is Data Science
00:13:33 - Roadmap to Data Science
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06:10:05 - Probability and Statistics
09:28:02 - Reinforcement Learning
- Classification of Machine Learning
- AI Agents Tutorial
- Data Science Interview Questions

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✅ About Post Graduate Program In Data Science:
This in-depth Data Science program is designed for working professionals, and covers job-critical topics like R, Python programming, Machine Learning techniques, NLP notions, and Data Visualization with Tableau, using an active learning model that includes live sessions from global professionals, practical labs, IBM Hackathons, and corporate ready projects

Key Features
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✅ Core curriculum delivered in live online classes by industry experts
✅ Industry-recognized IBM certificates for IBM courses
✅ Engage in live online masterclasses led by Industry Expert, staff, and IBM experts
✅ Exclusive hackathons and Ask Me Anything (AMA) sessions by IBM
✅ Gain exposure to ChatGPT, Gemini, Keras, TensorFlow and other prominent tools
✅ Interactive sessions on the latest AI trends, such as GenAI, prompt engineering, LLMs, and more
✅ 3 capstones and 25+ hands-on projects from various industry domains
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies

Skills Covered
✅ Exploratory Data Analysis
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✅ Data Visualization
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✅ Prompt Engineering
✅ ChatGPT
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✅ Machine Learning Algorithms
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
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Learning Path
✅ Program Induction
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✅ Data Management using SQL
✅ Python for Data Science (IBM)
✅ Applied Data Science with Python
✅ Machine Learning
✅ Deep Learning Specialization

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Data Science Full Course For Beginners 2026 by simplilearn is dedicated to help aspiring data scientists and data analysts about the fundamentals of data scientists. Learn Data Science In 12 Hours by Simplilearn will covet the following

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Tools & Technologies: Master the use of Python, R, SQL, and key data science libraries and frameworks.
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➡️ About Data Science Course in collaboration with IBM

This Data Science course in collaboration with IBM propels your career to become a data scientist. Gain expertise in in-demand skills like Python, SQL, Excel, Machine Learning, Tableau, generative AI, and more. Dive deep into data interpretation nuances, master Machine Learning, and enhance programming skills to elevate your Data Science career.

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In this video, we are diving into 10 mistakes and traps to avoid when learning data science and analytics. Do any of these resonate with you? Share in comments 👇🏽

# Subscribe https://www.youtube.com/sundaskhalid

# Watch this Next
https://youtube.com/playlist?list=PLNvMRDyXHRncmH4YJYcHhtLnxtqLOOm9o&si=Ut42VKeM9kW_T1N_
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0:00 intro
0:27 mistake 1
1:44 mistake 2
3:22 mistake 3
4:18 mistake 4
6:08 mistake 5
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8:52 mistake 9
9:28 mistake 10

# Social Media
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Some of the links included are affiliate links and help me keep this channel going. Thanks for the support. Business inquiries: partnerships@careerpy.com

#datascience

💠💠About this Specialization💠💠
his action-packed Specialization is for data science enthusiasts who want to acquire practical skills for real world data problems. If you’re interested in pursuing a career in data science, and already have foundational skills or have completed the Introduction to Data Science Specialization, this program is for you!

This 4-course Specialization will give you the tools you need to analyze data and make data driven business decisions leveraging computer science and statistical analysis. You will learn Python–no prior programming knowledge necessary–and discover methods of data analysis and data visualization. You’ll utilize tools used by real data scientists like Numpy and Pandas, practice predictive modeling and model selection, and learn how to tell a compelling story with data to drive decision making.

⭐⭐⭐⭐🕑TIME STAMP📋⭐⭐⭐⭐⭐
👉 👉PYTHON FOR DATA SCIENCE, AI & DEVELOPMENT
0:00:00 Types
0:03:02 Expressions and variables
0:06:57 String operations
0:10:56 Lists and tuples
0:19:47 Dictionaries
0:22:13 Sets
0:27:30 Conditionas and branching
0:37:47 Loops
0:44:33 Functions
0:58:05 Exception handling
1:01:55 Objects and Classes
1:12:47 Reading writing files with open
1:19:25 Pandas
1:24:35 Numpy in Python
1:43:12 Simple APIs
1:53:32 Rest APIs Webscraping and working with files

👉 👉PYTHON PROJECT FOR DATA SCIENCE
2:16:50 Optional intro to webscraping

👉 👉DATA ANALYSIS WITH PYTHON
2:26:50 Importing datasets
2:46:36 Data Wrangling
3:05:59 Exploratory data analysis
3:25:40 Model Development
3:53:05 Model Evaluation

👉 👉DATA VISUALIZATION WITH PYTHON
4:14:15 Introduction to Data Visualization Tools
4:40:54 Basic Visualization Tools
4:54:09 Specialized visualization Tools
5:06:58 Advanced Visualization tools
5:12:21 Visualizing Geospatial Data
5:21:40 Creating Dashboards with Plotly and dash

👉 👉APPLIED DATA SCIENCE CAPSTONE
5:39:10 Capstone introduction and understanding the datasets
5:42:19 Collecting the data
5:46:34 Data Wrangling
5:48:45 Exploratory analysis using SQL
5:50:46 Interactive visual analytics and dashboard
5:52:39 Predictive analysis classification
5:53:39 How to present your findings

♥️♥️Thanks for watching don't forget to like and Subscribe♥️♥️


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This video on Python for Data Science Full Course 2026 by Simplilearn, is designed to help beginners learn how Python is used in real-world data science projects. You’ll start with Python basics and gradually move into data analysis, data manipulation, and visualization using popular libraries like NumPy, Pandas, and Matplotlib. The course explains core data science concepts in simple terms with practical examples. You’ll also understand how Python supports data-driven decision-making across industries. By the end of this free course, you’ll be confident using Python for data science tasks and ready to move toward advanced analytics and machine learning. Perfect for students, professionals, and anyone starting a career in data science.

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✅ 2. Python RAG Tutorial 2026 - https://youtu.be/WQTaM7tBlvc
✅ 3. Data Science Roadmap For 2026 - https://youtu.be/ZpINzjm_4Ks
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➡️ About Applied Generative AI Specialization

This Applied Generative AI course equips you to develop AI-powered applications using industry-relevant tools and frameworks. Build expertise in key concepts like prompt engineering, GANs, VAEs, and LLM architectures while exploring advanced topics, including agentic AI, LLM fine-tuning, RAG, and AI governance for practical, real-world deployments.

Key Features

✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Program completion certificate from Simplilearn
✅ 70+ hours of live, instructor-led training with industry experts
✅ Hands-on learning with 7+ real-world projects and a capstone project
✅ Master in-demand skills like LLM fine-tuning, prompt engineering, and AI governance
✅ Gain expertise with cutting-edge tools such as ChatGPT, Azure AI Studio, and LangChain
✅ Comprehensive curriculum covering AI Literacy, Agentic Frameworks, and Generative AI
✅
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Course completion certificate hosted on the Microsoft Learn portal for Microsoft courses
✅ Learn with a diverse cohort of professionals from industries like IT, banking, and education

Skills Covered
✅ Python Programming
✅ Prompt Engineering
✅ AI Literacy
✅ Generative AI Fundamentals
✅ Large Language Model LLM Architecture
✅ Agentic AI and Autonomous AI Agents
✅ LangChain for Workflow Design
✅ Retrieval Augmented Generation RAG
✅ LLM Fine Tuning and Customization
✅ Stable Diffusion
✅ Explainable AI
✅ Variational Autoencoders VAEs
✅ Transformers and Attention Mechanism
✅ GenAI Application Development
✅ LLM Benchmarking and Evaluation
✅ Generative AI Governance and Ethics

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This video on Python for Data Science Full Course 2026 by Simplilearn, is designed to help beginners learn how Python is used in real-world data science projects. You’ll start with Python basics and gradually move into data analysis, data manipulation, and visualization using popular libraries like NumPy, Pandas, and Matplotlib. The course explains core data science concepts in simple terms with practical examples. You’ll also understand how Python supports data-driven decision-making across industries. By the end of this free course, you’ll be confident using Python for data science tasks and ready to move toward advanced analytics and machine learning. Perfect for students, professionals, and anyone starting a career in data science.

Following are the topics covered in the Python for Data Science Full Course 2026:

00:00:00 - Introduction Python for Data Science Full Course 2026
00:02:51 - Data science pipeline and deployment demo
00:13:52 - NumPy fundamentals and array basics
00:46:07 - NumPy operations and special arrays
01:16:16 - Random numbers, arange/reshape, broadcasting
01:41:50 - Linear algebra and NumPy utilities
02:05:39 - Pandas: Series and DataFrame basics
02:34:10 - Reading data and practical I/O
03:01:12 - DataFrame EDA and exploration
03:25:26 - Indexing, feature engineering, sorting, cleaning
04:26:15 - GroupBy, pivot tables, and filtering
05:01:13 - Concatenation and merges
05:29:28 - Matplotlib fundamentals and chart choices
06:19:47 - Seaborn and Plotly visualizations
08:21:40 - Statistics foundations: variables and central tendency
09:15:06 - Dispersion, scaling, distributions, correlation, probability

Related Videos:
✅ 1. Python Full Course 2026 - https://youtu.be/lRfjnTYJnJ8
✅ 2. Python RAG Tutorial 2026 - https://youtu.be/WQTaM7tBlvc
✅ 3. Data Science Roadmap For 2026 - https://youtu.be/ZpINzjm_4Ks
✅ 4. FREE Data Scientist Course - https://youtu.be/_NsDrON32ww
✅ 5. Data Science Interview Questions - https://youtu.be/vtCwJKUhizg

✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

⏩ Check out More AI Videos By Simplilearn: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULyr_

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➡️ About Applied Generative AI Specialization

This Applied Generative AI course equips you to develop AI-powered applications using industry-relevant tools and frameworks. Build expertise in key concepts like prompt engineering, GANs, VAEs, and LLM architectures while exploring advanced topics, including agentic AI, LLM fine-tuning, RAG, and AI governance for practical, real-world deployments.

Key Features

✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Program completion certificate from Simplilearn
✅ 70+ hours of live, instructor-led training with industry experts
✅ Hands-on learning with 7+ real-world projects and a capstone project
✅ Master in-demand skills like LLM fine-tuning, prompt engineering, and AI governance
✅ Gain expertise with cutting-edge tools such as ChatGPT, Azure AI Studio, and LangChain
✅ Comprehensive curriculum covering AI Literacy, Agentic Frameworks, and Generative AI
✅ Skills Covered
✅ Python Programming
✅ Prompt Engineering
✅ AI Literacy
✅ Generative AI Fundamentals
✅ Large Language Model LLM Architecture
✅ Agentic AI and Autonomous AI Agents
✅ LangChain for Workflow Design
✅ Retrieval Augmented Generation RAG
✅ LLM Fine Tuning and Customization
✅ Stable Diffusion
✅ Explainable AI
✅ Variational Autoencoders VAEs
✅ Transformers and Attention Mechanism
✅ GenAI Application Development
✅ LLM Benchmarking and Evaluation
✅ Generative AI Governance and Ethics

👉 Enroll Now: https://www.simplilearn.com/applied-ai-course?utm_campaign=bN_H9uUFSWo&utm_medium=Description&utm_source=Youtube

🔥🔥 Interested in Attending Live Classes? Call Us: IN - 18002127688 / US - +18445327688

Step into the world of Data Science with our comprehensive video designed for beginners. We’ll cover everything you need to start your journey, from understanding the Data Science Life Cycle to exploring roles like Data Analyst, Data Scientist, and Data Engineer. Learn essential Python libraries, core statistics concepts, and key Machine Learning algorithms. Discover the role of SQL in data management and get introduced to Generative AI and ChatGPT. We’ll also guide you through practical Data Science projects and prep you for job interviews. Watch now and start building your skills today!

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🏁 Topics Covered:
00:00:00 Introduction
00:01:18 What is Data Science
00:03:07 Data Science Life Cycle
00:08:01 Data Analyst vs Data Scientist vs Data Engineer
00:10:24 Numpy
00:10:51 Creating and Intializing Numpy Array
00:21:21 Numpy Shape
00:23:43 Joinig Numpy arrays
00:27:12 Numpy Intersection and Differences
00:30:49 Numpy Array Mathematics
00:38:17 Numpy Matrix
00:41:32 Numpy Matrix Transpose and Multiplication
00:44:46 Numpy Save and Load
00:46:44 Pandas
00:47:10 Pandas Series Object
00:49:32 Changing Index
00:50:49 Series object from Dictionary
00:53:01 Extracting Individual Elements
00:57:39 Pandas Dataframe
00:58:15 Creating a Dataframe
01:00:36 Dataframe In-build Function
01:03:07 .iloc and loc function
01:07:02 Dropping Columns
01:08:22 Dropping rows
01:11:00 Matplotlib
01:11:12 Line plot
01:25:18 Bar plot
01:31:38 Scatter Plot
01:39:33 Histogram
01:46:15 Seaborn Line Plot
01:54:24 Seaborn Bar Plot
02:02:24 Seaborn Scatter Plot
02:07:38 Seaborn Histogram/ Distplot
02:16:56 Types of Statistical Analysis
02:22:29 Inferential Statistics
02:24:56 Descriptive Statistics
02:29:12 Measures of Central Tendency
02:37:40 Measures of Variability
02:43:03 Measures of Relationship
02:48:30 Measures of Skewness
02:51:33 Analysis of Variance
02:56:56 ANOVA Define
03:06:11 Grand Mean
03:10:12 F-Ratio
03:12:16 Hypothesis Testing
03:13:17 Types of Hypothesis Testing
03:18:25 Important Terms in Hypothesis Testing
03:20:30 ANOVA vs.T-test
03:22:06 Applications of ANOVA Test
03:23:01 Machine Learning
03:23:32 Supervised Learning
03:29:39 Unsupervised Learning
03:33:59 Reinforcement Learning
03:37:45 Clustering
03:39:20 Examples of Clustering
03:39:50 Need of Clustering
03:40:42 Types of Clustering
03:43:47 K-Means Clustering
03:44:51 Applications of K-means
03:51:55 Deciding value of K
03:53:00 Elbow Method
03:54:34 Implementation of K-means Clustering
04:19:16 Regression
04:21:24 Use case of Regression
04:23:05 Linear Regression
04:25:14 Multi Linear Regression
04:27:10 Types of Linear Regression
04:31:54 Demo - Simple Linear Regression
04:42:53 Demo- Multiple Linear Regression
05:25:09 Logistic Regression
05:30:23 Use Cases of Logistic Regression and its Demo
06:07:07 Installing MySQL
06:18:00 DML Command
06:48:39 DCL Command
06:56:50 TCL Commands
06:58:10 Joins in MySQL
07:00:14 INNER Join
07:50:17 Full Join
07:59:22 SELF Join
08:06:15 Subquery and Types
08:09:17 Demo on Subqueries
08:36:14 ALL Operators
09:04:06 Need of Gen AI in Data Science
09:05:54 Projects on Data Science
09:50:53 Top Data Science Interview Questions
10:20:23 Summary

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This Data Science Full Course Video by Simplilearn provides a detailed roadmap to learn data science. It begins with an introduction to data science and explores the future scope of AI. You’ll learn the skills to becoming a data scientist and dive into key topics like AI bias. The course also explains the differences between AI, ML, and DL (Artificial Intelligence, Machine Learning, and Deep Learning) and introduces deep learning and applied data science with Python. Additionally, it covers running Lama privately, understanding LLMs (Large Language Models) and their benchmarking, and working with LangChain. The video concludes with insights into the confusion matrix, beginner-friendly machine learning projects, and essential interview questions, offering a holistic learning experience for aspiring data scientists.

00:00:00 Introduction to Data Science Full Course
00:04:21 What is Data Science
00:05:55 How To Learn AI and Machine Learning
00:14:36 How to become Data Scientist
00:29:29 AI Bias Tutorial For Beginners
00:35:40 Difference between AI Machine Learning and Deep Learning
00:45:16 Roadmap to Data Science
01:31:35 Probability and Statistics
01:40:52 How To Learn Data Science Fast
06:51:05 Deep Learning
06:52:12 How to Run Lama Privately
07:00:56 Introduction to Large Language Models
07:14:25 LLM Benchmarking Tutorial
07:15:44 Lang chain Tutorial
07:43:12 Confusion Matrix in Machine Learning
07:44:02 Q Learning
08:16:19 Stable diffusion
09:23:16 Data Science Interview Questions

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➡️ About Data Science Course in collaboration with IBM

This Data Science course in collaboration with IBM propels your career to become a data scientist. Gain expertise in in-demand skills like Python, SQL, Excel, Machine Learning, Tableau, generative AI, and more. Dive deep into data interpretation nuances, master Machine Learning, and enhance programming skills to elevate your Data Science career.

Key Features
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Masterclasses from IBM experts
✅ Dedicated live sessions by faculty of industry experts
✅ Industry-recognized Data Scientist Master’s certificate from Simplilearn
✅ Industry-recognized IBM certifications for IBM courses
✅ Ask-Me-Anything (AMA) sessions with IBM leadership
✅ Capstone from 3 domains and 25+ projects
✅ Exclusive hackathons conducted by IBM
✅ Lifetime access to self-paced learning content
✅ Program crafted to initiate your journey as a Data Scientist
✅ Integrated labs for hands-on learning experience

Skills Covered
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Explainable AI
✅ Conversational AI
✅ Large Language Models
✅ Model Building and Finetuning
✅ Ensemble Learning
✅ Data Visualization
✅ Database Management

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🔥🔥

What data science is about!

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This Data Science Full Course 2025 by Intellipaat is a complete learning path to master data science from scratch. It starts with an introduction to what is data science, then takes you through the basic Python understanding you need to get started in Data Science. Followed by that, you will go through hands-on sessions for learning libraries like Pandas and Matplotlib for data analysis and visualization. As you advance, you'll explore Exploratory Data Analysis (EDA) and understand different types of machine learning algorithms.

The course covers key ML models such as Linear Regression, Logistic Regression, Support Vector Machines (SVM), Decision Trees, and K-Means Clustering, each explained step by step. You’ll also build a real-world Data Science project (Recommendation System) and prepare for the job market with a detailed session on Data Science Interview Questions. Whether you're a beginner or switching careers, this complete data science course equips you with the practical skills to become job-ready in 2025.

Below are the topics covered in Data Science Full Course 2025:
00:00:00 - Introduction to Data Science Full Course
00:01:33 – What is Data Science?
00:06:26 – Python for Data Science
00:09:06 – Pandas for Data Science
01:15:09 – Data Visualization with Matplotlib
02:05:33 – Exploratory Data Analysis (EDA)
02:44:30 – Types of Machine Learning
02:56:51 – Linear Regression
06:13:00 – Logistic Regression
06:53:27 – Support Vector Machine (SVM)
06:55:09 – Decision Tree
06:57:27 – Clustering (K-Means)
07:52:07 – Data Science Project Walkthrough
09:13:31 – Data Science Interview Questions

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🔗 Supporting Media (The Detailed Deep-Dive Material)
1. Logistic Regression: https://youtu.be/29F-fXvowoI
2. SVM : https://youtu.be/2I8TJBfGml0
3. Decision Tree: https://youtu.be/JmAVQ5fDikk

➡️ About Data Science Course:
This online Data Science course, in collaboration with iHUB, IIT Roorkee & Microsoft, will help you to elevate your Data Science career. In this course, you will master skills like Python, SQL, Statistics, Machine Learning, AI, Power BI & Generative AI, along with real-time industry-oriented projects.

➡️ Key Features:
✅ 50+ Live interactive sessions across 7 months
✅ 218 Hrs Self-paced Videos
✅ 50+ Industry relevant Projects & Quizzes
✅ Live Classes from IIT Faculty & Industry Experts
✅ Certification from iHub IIT Roorkee & Microsoft
✅ 2 Days Campus Immersion at iHub IIT Roorkee

➡️ What’s Covered in This Program?
✅ Linux and Python Fundamentals
✅ Data Wrangling with SQL
✅ Python with Data Science
✅ Linear Algebra and Advanced Statistics
✅ Machine Learning and Prediction Algorithms
✅ Supervised and Unsupervised Learning in ML
✅ Deep Learning with TensorFlow
✅ Generative AI & Prompt Engineering
✅ Deploying Machine Learning Models on Cloud
✅ Data Visualization Tool Power BI

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Can you learn Data Science - even if you don't know Python - in just an hour? YES. In this complete tutorial, you'll learn the basics of data science and Python as you work with student data to predict a grade based on the number of hours studied.

Chapters:
Part 1:
00:00 Getting started with Visual Studio Code and Anaconda
01:09 Installing Jupyter Notebooks and Python
01:32 Creating a Jupyter Notebook
02:17 Working with data
09:27 Introduction to Pandas
10:18 Working with Data Frames
14:18 Read a CSV file into a Pandas Data Frame
15:31 Remove Null values in data
19:57 Adding a column to a Data Frame
21:26 Grouping data using 'groupby()'
Part 2:
25:16 Creating charts from data
26:12 Rainbow CSV
26:31 Using Matplotlib to make charts
28:02 Customizing charts with Matplotlib
32:18 Creating a pie chart with Matplotlib
34:12 Creating a chart directly from Data Frame
34:58 Data Science, Samples, and Distributions
35:45 Creating a histogram with Matplotlib
37:39 Central Tendencies, Mean, Median, and Mode
41:21 Creating a boxplot with Matplotlib
43:57 Visualizing probability density with Matplotlib
Part 3:
46:22 Creating a Jupyter Notebook
47:06 Statistical Outliers
49:22 Variance, Range, and Standard Deviation
52:39 68% Rule
56:37 Analyzing box plots
58:46 Normalizing ranges
01:02:17 Calculating Correlation value
01:04:19 Using regression lines
01:06:00 Least squares regression
01:09:54 Things are getting interesting
01:12:16 Thank you for learning with us!

Follow along with the interactive tutorial 👉 https://aka.ms/data-science-from-scratch

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This Data Science Python Full Course 2026 by Simplilearn begins with an introduction to Python, setting the stage for why it's a powerful and popular language in today's tech landscape. Learners are then guided through the fundamentals, including what Python is and how it is used across industries. The course unboxes a comprehensive Data Science curriculum and outlines a clear roadmap to becoming a data science professional. It also explains what Data Science is and how Python plays a crucial role in it. After covering installation and setup, learners write their first Python program, building a strong foundation for hands-on coding. The course progresses to essential real-world applications, such as Exploratory Data Analysis (EDA), web scraping, and working with REST APIs using Python. To solidify learning, five top Python projects are demonstrated, giving practical exposure to coding challenges. Finally, the course concludes with key Python interview questions to help learners prepare for job opportunities and technical assessments.

The Python For Data Analytics Full Course video covers the following topics.

00:00:00 - Introduction to Python For Data Science Full Course 2026
00:04:21 - What is Data Science
00:10:31 - Data science course unboxing
00:19:43 - Roadmap to Data Science
00:37:05 - What is Python
00:43:35 - how to Install Python
06:35:07 - Data Science basics
06:36:31 - Introduction to LLM
07:15:10 - EDA Using Python
07:16:28 - Web Scraping Project in Python
11:40:24 - Data Science Interview Questions

✅ Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

⏩ Check out the Data Science tutorial videos: https://www.youtube.com/watch?v=X3paOmcrTjQ&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6

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➡️ About Data Science Course in collaboration with IBM

This Data Science course in collaboration with IBM propels your career to become a data scientist. Gain expertise in in-demand skills like Python, SQL, Excel, Machine Learning, Tableau, generative AI, and more. Dive deep into data interpretation nuances, master Machine Learning, and enhance programming skills to elevate your Data Science career.

Key Features
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Masterclasses from IBM experts
✅ Dedicated live sessions by faculty of industry experts
✅ Industry-recognized Data Scientist Master’s certificate from Simplilearn
✅ Industry-recognized IBM certifications for IBM courses
✅ Ask-Me-Anything (AMA) sessions with IBM leadership
✅ Capstone from 3 domains and 25+ projects
✅ Exclusive hackathons conducted by IBM
✅ Lifetime access to self-paced learning content
✅ Program crafted to initiate your journey as a Data Scientist
✅ Integrated labs for hands-on learning experience

Skills Covered
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Explainable AI
✅ Conversational AI
✅ Large Language Models
✅ Model Building and Finetuning
✅ Ensemble Learning
✅ Data Visualization
✅ Database Management

👉 Learn More At: https://www.simplilearn.com/iitk-professional-certificate-course-data-analytics?utm_campaign=WU-UrrP2OWU&utm_medium=Lives&utm_source=Youtube

🔥🔥

Welcome to Part 1 of our comprehensive Python for Data Science full course! This 10+ hour video is packed with over 5 real-world projects to help you master Python and apply it effectively in data science.
Link to Download Notes - https://www.theiscale.com/cour....se-details/full-stac

In this video

00:03.27 - Intro
03:28 - How To Download Notes
08:06 - Python for Data Science Part 1 Full Course Overview
11:07 - Lecture No. 1 : Fundamentals of Data Science
1:13:54 - Lecture No. 2 : Variables & Data Types
2:04:20 - Lecture No. 3 : Operators in Python
3:05:21 - Lecture No. 4 : Built in Functions part 1
3:50:28 - Lecture No. 5 : Built in Functions part 2
4:46:51 - Lecture No. 6 : Special Interview Based Class
5:26:38 - Lecture No. 7 : Control Flow Statements
6:16:22 - Lecture No. 8 : Loops in Python part 1
6:50:38 - Lecture No. 9 : Loops in Python part 2
7:35:15 - Lecture No. 10 : User Defined Functions
8:14:27 - Lecture No. 11 : Special Interview Based Class
8:56:34 - Lecture No. 12 : Strings in Python part 1
9:38:22 - Lecture No. 13 : Strings in Python part 2
Libraries : Numpy, Pandas , Matplotlib, Seaborn, Plotly
5+ Projects

✨ Kickstart your career in a Data Science & Data Analyst. Apply today! - https://www.theiscale.com/Data....Analytics/data-analy

Stay Tuned for the upcoming parts 🎉

📚 Course Overview: Get an introduction to the course structure and what you can expect to learn.

🐍 Python Basics: Start with the fundamentals of Python programming, including variables, data types, and control structures.

🔄 Data Structures: Dive deep into essential data structures such as lists, dictionaries, and tuples.

📈 Data Manipulation: Learn how to manipulate and analyze data using powerful Python libraries like Pandas and NumPy.

🔍 Data Visualization: Discover how to create compelling data visualizations using Matplotlib and Seaborn.

🛠️ Real-World Projects: Apply your skills with hands-on projects that cover various data science problems, from data cleaning to building machine learning models.

🌟 Additional Resources: Access further resources and materials to enhance your learning experience.

✨Lecture 1 to 13 Notes - https://www.theiscale.com/cour....se-details/free-100-
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Whether you're a beginner or looking to solidify your knowledge, this course will provide you with the skills and confidence to tackle data science projects using Python. Don’t forget to like, comment, and subscribe for more parts and updates!

#Python #DataScience #FullCourse #LearnPython #DataScienceProjects #PythonProgramming #Pandas #NumPy #Matplotlib #Seaborn #TechEducation #DataAnalysis #MachineLearning

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This Data Science Full Course Video by Simplilearn helps you learn a brief introduction to data science. followed by that, we will continue by discussing the scope of AI in future, then we will learn the roadmap to become a data scientist, followed by that, we will learn the AI BIAS topic, proceeding ahead we will learn the differences between AI, ML, and DL (Artificial intelligence vs machine learning vs deep learning), next we will have a brief introduction to deep learning and applied data science with python. Then we will learn how to Run Lama Privately. Afterwards, we will procced with an Introduction to LLm and LLM benchmarking, we will proceed with LangChain. Lastly we will discuss Confusion matrix, Machine learning projects for beginners and at the end we will discuss important interview questions. The video covers the following topics.

00:00:00 Introduction to Data Science Full Course
00:04:21 Data Science in 5 minutes
00:13:27 Future of AI
00:14:59 How to become Data Scientist
00:29:52 AI Bias
00:36:03 Difference between AI ML and DL
00:45:39 Roadmap to Data Science
00:54:56 Fastest way to Learn Data Science
06:48:37 Deep Learning
10:05:37 Applied Data Science with Python
10:06:44 Run Lama Privately
10:15:28 Introduction to LLM
10:28:57 LLM Benchmarking
10:30:16 Lang Chain Explained
10:57:44 Confusion Matrix ML
11:15:29 ML Projects for Beginners
12:22:26 Interview Questions

✅ Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

⏩ Check out the Data Science tutorial videos: https://www.youtube.com/watch?v=X3paOmcrTjQ&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6

#datascience #datasciencecourse #datascienceroadmap #datascientist #datascienceforbeginners #datasciencetools #simplilearn #2024

What is Data Science?
Data science is the field of study that works with massive amounts of data utilizing relevant tools and techniques to derive valuable data. Companies across various industries generate vast amounts of data, so its applications range all the way from education, healthcare, and entertainment to Finance and Marketing.

✅ About Post Graduate Program In Data Science:
This in-depth Data Science program is designed for working professionals, and covers job-critical topics like R, Python programming, Machine Learning techniques, NLP notions, and Data Visualization with Tableau, using an active learning model that includes live sessions from global professionals, practical labs, IBM Hackathons, and corporate ready projects

Key Features
✅
✅
✅ Core curriculum delivered in live online classes by industry experts
✅ Industry-recognized IBM certificates for IBM courses
✅ Engage in live online masterclasses led by Industry Expert, staff, and IBM experts
✅ Exclusive hackathons and Ask Me Anything (AMA) sessions by IBM
✅ Gain exposure to ChatGPT, Gemini, Keras, TensorFlow and other prominent tools
✅ Interactive sessions on the latest AI trends, such as GenAI, prompt engineering, LLMs, and more
✅ 3 capstones and 25+ hands-on projects from various industry domains
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies

Skills Covered
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Model Building and Finetuning
✅ Supervised and Unsupervised Learning
✅ Ensemble Learning
✅ Deep Learning
✅ Data Visualization
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Explainable AI
✅ Machine Learning Algorithms
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
✅ Speech Recognition

Learning Path
✅ Program Induction
✅ Programming Refresher
✅ Data Management using SQL
✅ Python for Data Science (IBM)
✅ Applied Data Science with Python
✅ Machine Learning
✅ Deep Learning Specialization

👉 Enroll Now: https://www.simplilearn.com/in/data-analyst-course?utm_campaign=dAkZTYgPBsw&utm_medium=Lives&utm_source=youtube

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This video on Python libraries for the Data Science course will make you understand how to perform numerical computation, data analysis, and data visualization using NumPy, Pandas, and Matplotlib libraries. You will so get an idea about Scikit Learn for model building, BeautifulSoup for Web Scrapping. Finally, you will learn about TensorFlow.

Below are the topics we will be discussing in this video:
00:00:00 Top 5 Python Libraries for Data Science
00:16:34 NumPy
01:39:06 Pandas
02:31:37 Matplotlib
03:32:58 Web Scrapping Using Python
04:10:15 Scikit-Learn Tutorial
04:53:55 Tensorflow 2.0

✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

⏩ Check out the Data Science tutorial videos: https://www.youtube.com/watch?v=X3paOmcrTjQ&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6

#PythonLibrariesForDataScience #PythonLibrariesForBeginners #PythonLibrariesExplained #PythonLibrariesTutorial #DataScienceTutorial #DataScience #Simplilearn

➡️ About Data Science Course in collaboration with IBM

This Data Science course in collaboration with IBM propels your career to become a data scientist. Gain expertise in in-demand skills like Python, SQL, Excel, Machine Learning, Tableau, generative AI, and more. Dive deep into data interpretation nuances, master Machine Learning, and enhance programming skills to elevate your Data Science career.

Key Features
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Masterclasses from IBM experts
✅ Dedicated live sessions by faculty of industry experts
✅ Industry-recognized Data Scientist Master’s certificate from Simplilearn
✅ Industry-recognized IBM certifications for IBM courses
✅ Ask-Me-Anything (AMA) sessions with IBM leadership
✅ Capstone from 3 domains and 25+ projects
✅ Exclusive hackathons conducted by IBM
✅ Lifetime access to self-paced learning content
✅ Program crafted to initiate your journey as a Data Scientist
✅ Integrated labs for hands-on learning experience

Skills Covered
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Explainable AI
✅ Conversational AI
✅ Large Language Models
✅ Model Building and Finetuning
✅ Ensemble Learning
✅ Data Visualization
✅ Database Management

👉 Learn More At: https://www.simplilearn.com/in/data-analyst-course?utm_campaign=DataScience-Ee8dDnwq374&utm_medium=Description&utm_source=youtube

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This Data Science Python Full Course 2026 by Simplilearn begins with an introduction to Python, setting the stage for why it's a powerful and popular language in today's tech landscape. Learners are then guided through the fundamentals, including what Python is and how it is used across industries. The course unboxes a comprehensive Data Science curriculum and outlines a clear roadmap to becoming a data science professional. It also explains what Data Science is and how Python plays a crucial role in it. After covering installation and setup, learners write their first Python program, building a strong foundation for hands-on coding. The course progresses to essential real-world applications, such as Exploratory Data Analysis (EDA), web scraping, and working with REST APIs using Python. To solidify learning, five top Python projects are demonstrated, giving practical exposure to coding challenges. Finally, the course concludes with key Python interview questions to help learners prepare for job opportunities and technical assessments.

The Python For Data Analytics Full Course video covers the following topics.

00:00:00 - Introduction to Python For Data Science Full Course 2026
00:04:21 - What is Data Science
00:10:31 - Data science course unboxing
00:19:43 - Roadmap to Data Science
00:37:05 - What is Python
00:43:35 - how to Install Python
06:35:07 - Data Science basics
06:36:31 - Introduction to LLM
07:15:10 - EDA Using Python
07:16:28 - Web Scraping Project in Python
11:40:24 - Data Science Interview Questions

✅ Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

⏩ Check out the Data Science tutorial videos: https://www.youtube.com/watch?v=X3paOmcrTjQ&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6

#python #pythonprogramming #pythontutorial #pythonforbeginners #python3 #pythonprojects #pythoncoding #pythonfullstack #pythonfullcourse #simplilearn #2026

➡️ About Data Science Course in collaboration with IBM

This Data Science course in collaboration with IBM propels your career to become a data scientist. Gain expertise in in-demand skills like Python, SQL, Excel, Machine Learning, Tableau, generative AI, and more. Dive deep into data interpretation nuances, master Machine Learning, and enhance programming skills to elevate your Data Science career.

Key Features
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Masterclasses from IBM experts
✅ Dedicated live sessions by faculty of industry experts
✅ Industry-recognized Data Scientist Master’s certificate from Simplilearn
✅ Industry-recognized IBM certifications for IBM courses
✅ Ask-Me-Anything (AMA) sessions with IBM leadership
✅ Capstone from 3 domains and 25+ projects
✅ Exclusive hackathons conducted by IBM
✅ Lifetime access to self-paced learning content
✅ Program crafted to initiate your journey as a Data Scientist
✅ Integrated labs for hands-on learning experience

Skills Covered
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Explainable AI
✅ Conversational AI
✅ Large Language Models
✅ Model Building and Finetuning
✅ Ensemble Learning
✅ Data Visualization
✅ Database Management

👉 Learn More At: https://www.simplilearn.com/iitk-professional-certificate-course-data-analytics?utm_campaign=Dwtv_K_EmzQ&utm_medium=Lives&utm_source=Youtube

🔥🔥

Go to https://bit.ly/Hands-onDataSciencewithPython to master Python for Data Science with a 7-day free Pro+ trial—get job-ready with AI resume builder, mock interviews, hands-on projects & real-world datasets.

Skills Covered:
🌟Python programming basics & OOP
🌟Data handling & manipulation with NumPy and Pandas
🌟Data visualization using Matplotlib and Seaborn
🌟Statistics and foundations of Data Science
🌟Supervised and Unsupervised Learning
🌟Regression techniques (Linear & Logistic)
🌟Time Series Analysis
🌟Real-world projects with Python

🏁 YouTube Video Chapters with Timestamps:
00:00 – Introduction
02:59 – Python Installation & Setup (PyCharm, Anaconda, Jupyter Notebook)
11:15 – Variables & Data Types
18:52 – Operators in Python
26:43 – Data Structures (Tuple, List, Dictionary, Set)
01:20:21 – Flow Control Statements
01:44:34 – Functions
01:59:32 – Object-Oriented Programming & Inheritance
02:49:55 – Python Libraries: NumPy, Pandas
03:50:03 – Data Visualization: Matplotlib & Seaborn
05:26:01 – Python Project: IPL Data
06:01:26 – Python Project: FIFA
06:22:23 – Python Project: Marvel/DC Characters
06:36:44 – Introduction to Data Science & Machine Learning
06:56:34 – Supervised & Unsupervised Learning
07:39:11 – Regression Techniques
09:31:53 – Time Series Analysis

Related Free Python & Data Science Learning:
🐍 Python Uses: https://bit.ly/GLAPythonforDataScience
📊 Python for Data Science: https://bit.ly/GLAPythonforDataScience
🖥️ Python Projects for Data Analysis: https://bit.ly/PythonProjectsforDataAnalysis
🔍 Data Science with Python: https://bit.ly/FreeDataSciencewithPythonCourse
📈 Data Visualization using Python: https://bit.ly/DataVisualizationinPython

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Looking to start a career in data science in 2025? This Data Science Full Course by Intellipaat is your one-stop solution to mastering the entire data science lifecycle, from fundamentals to building real-world AI applications. Start with a clear understanding of what is data science and the data science lifecycle, followed by a detailed roadmap to become a data scientist. You’ll learn essential tools like Python and Pandas for data manipulation, then dive deep into Exploratory Data Analysis (EDA) to make sense of data.

Advance your skills with hands-on tutorials in machine learning algorithms such as Linear Regression, Logistic Regression, SVM, Decision Trees, and K-Means Clustering. This course also features an end-to-end data science project, expert career tips, real data science interview questions, and even a session on building your own AI agent. Bonus: Learn how to set up and work with an MCP server. Whether you're a beginner or looking to upskill, this course will help you become job-ready and build a successful career in data science.

Below are the topics covered in Data Science Full Course 2025:
00:00:00 - Introduction to Data Science Course
00:06:24 - What is Data Science?
00:10:51 - Data Science Lifecycle
00:13:36 - Roadmap to Become a Data Scientist
00:26:00 - Python for Data Science
00:28:41 - Pandas for Data Manipulation
01:34:42 - Understanding EDA
02:13:40 - Types of Machine Learning
02:26:25 - Linear Regression
05:42:34 - Logistic Regression
06:23:01 - Support Vector Machine (SVM)
06:24:42 - Decision Tree
06:27:18 - Clustering with K-Means
07:22:30 - End-to-End Data Science Project
08:43:05 - Expert Tips: How to Kickstart Your Data Science Journey
09:30:51 - Data Science Interview Questions
10:36:05 - Building an AI Agent from Scratch
10:57:21 - MCP Server Tutorial

#datasciencefullcourse #datasciencecourse #datasciencetraining #intellipaat

🔥Register for Intellipaat's Premium Data Science Course: https://intellipaat.com/data-s....cientist-course-trai

➡️ About Data Science Course:
This online Data Science course, in collaboration with iHUB, IIT Roorkee & Microsoft, will help you to elevate your Data Science career. In this course, you will master skills like Python, SQL, Statistics, Machine Learning, AI, Power BI & Generative AI, along with real-time industry-oriented projects.

➡️ Key Features:
✅ 50+ Live interactive sessions across 7 months
✅ 218 Hrs Self-paced Videos
✅ 50+ Industry relevant Projects & Quizzes
✅ Live Classes from IIT Faculty & Industry Experts
✅ Certification from iHub IIT Roorkee & Microsoft
✅ 2 Days Campus Immersion at iHub IIT Roorkee

➡️ What’s Covered in This Program?
✅ Linux and Python Fundamentals
✅ Data Wrangling with SQL
✅ Python with Data Science
✅ Linear Algebra and Advanced Statistics
✅ Machine Learning and Prediction Algorithms
✅ Supervised and Unsupervised Learning in ML
✅ Deep Learning with TensorFlow
✅ Generative AI & Prompt Engineering
✅ Deploying Machine Learning Models on Cloud
✅ Data Visualization Tool Power BI

🔥🔥 Interested in Attending Live Classes? Call Us: IND: +91-7022374614 / US: 1-800-216-8930

🔥Intellipaat Data Science course: https://intellipaat.com/data-s....cience-architect-mas
Intellipaat Data Science Course is a free Data Science tutorial for beginners as well as professionals to learn Data Science and its algorithms in a comprehensive crash course. This complete Data Science course masters you to learn the Data Science principles, tools, algorithms, and methodologies that make it a powerful medium to solve business problems.

➡Below are the topics covered in this Data Science for Beginners Course video:
00:00 - Data Science Course
01:45 - Who is a Data Scientist?
03:03 - Where do Data Scientist come from?
05:34 - What does a Data Scientist do?
09:00 - Prerequisites to become a Data Scientist
13:12 - Data Scientist Roles and Responsibilities
19:17 - Data Scientist Salary
21:05 - Who's hiring Data Scientist?
22:51 - Need of Data Science
24:13 - What is Data science?
25:14 - Understanding Different Techniques
25:21 - Data Visualization
25:39 - Data manipulation
26:05 - Statistical Analysis
26:25 - Machine Learning
28:09 - Life Cycle of Data Science
28:23 - Data Acquisition
28:50 - Data Preprocessing
29:06 - Model building
29:22 - Pattern Evaluation
29:44 - Knowledge Representation
30:03 - Chat-Bots
30:45 - Sentiment Analysis
31:08 - Image - Tagging
31:25 - What is Numpy?
33:21 - How to Create Numpy Array?
39:37 - Numpy Array Initialization
47:00 - Numpy Array Inspection
01:06:50 - Numpy Broadcasting
01:09:40 - Indexing and Slicing in Python
01:15:23 - Array Manipulation in Python
01:36:30 - Advantages of Numpy over List
01:45:56 - Pandas Module
01:46:50 - What is Pandas?
01:48:24 - Where did the name pandas come from?
01:49:55 - Features of Pandas
01:56:20 - Pandas vs Numpy
01:58:24 - How to import Pandas in Python?
01:59:09 - Data Structure in Pandas
02:00:29 - What is series object?
02:03:00 - How to change the Index name?
02:05:16 - What is a DataFrame?
02:06:03 - Features of DataFrame
02:07:27 - How to Create DataFrame?
02:18:40 - Merge, Join and Concatenate
02:56:00 - Quiz
02:58:45 - Basics of Data Visualization
03:05:45 - Plotting the graphs (Matplotlib Demo)
03:13:33 - Data Visualization Libraries
03:15:35 - What is Matplotlib?
03:16:20 - Why choose Matplotlib?
03:21:45 - Types of Plots and Demo on Matplotlib
04:29:55 - Introduction to Machine Learning
04:41:46 - What is Machine Learning?
04:43:30 - How does Machine Learn?
04:45:16 - Machine Learning popular Myth!
04:47:31 - Types of Machine Learning
04:48:05 - Supervised Learning
04:51:26 - Unsupervised Learning
04:59:36 - Reinforcement Learning
05:11:26 - Types of Regression
06:23:45 - Logistic Regression
06:44:27 - Spam Email Classifier
07:55:55 - What is Classification
07:56:47 - Types of Classification
08:08:11 - Visualizing a Decision Tree
08:10:00 - Decision Tree Terminology
08:14:35 - Creating a Decision Tree
08:16:00 - How do we split a Tree?
08:17:55 - Calculating Entropy
08:33:56 - Confusion Matrix
08:36:00 - Decision Tree Example Hands-on
08:45:10 - Understanding Naive Bayes Classifier
09:02:44 - Clustering algorithms
09:03:38 - What is Clustering?
09:04:57 - Examples of Clustering
09:08:20 - Types of Clustering
09:12:40 - K means Clustering
09:12:04 - What us k-means Clustering?
09:15:24 - Business Application of K-Means
09:16:36 - Understanding K-means Algorithm
09:34:27 - Python Project
10:33:50 - Python Interview Questions
11:21:57 - Machine Learning with Python
11:30:27 - Data Science Project
12:11:30 - Quiz
12:11:50 - Data Science Interview Questions

📕 Read complete Data Science tutorial here: https://intellipaat.com/blog/t....utorial/data-science
#DataScienceCourse #DataScienceFullCourse #DataScienceforBeginners #DataScienceTutorial

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📰Interested to know about Data Science certifications? Read this blog: https://intellipaat.com/blog/d....ata-science-certific
----------------------------
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This Data Science Full Course 2025 by Simplilearn, we start with a beginner-friendly introduction to Data Science, guiding you through its basics and how to start a career in this field. You’ll learn the roadmap to becoming a data scientist, starting with Probability and Statistics, a core foundation for analysis. The course then covers Data Science essentials, including Python basics, understanding Artificial Intelligence, Machine Learning, and Deep Learning, key roles like Data Analyst vs Data Scientist, and important concepts like distributions, Bayes Theorem, and the Data Science life cycle. We’ll dive deeper into Machine Learning, exploring algorithms like Decision Trees, Random Forests, K-Means, Naive Bayes, and Deep Learning. Finally, the course wraps up with top interview questions to prepare you for real-world roles in Data Science.

Following are the topics covered in Data Science Full Course 2025:

00:00:00 - Introduction to Data Science Full Course 2025
00:44:13 - Data Science Tutorial For Beginners
00:50:23 - Professional certificate course in Data Science
00:59:35 - Roadmap to Data Science
01:45:54 - Probability and Statistics
07:37:26 - Data Science Basics
• Introduction to Data Science
• Al vs ML vs DL vs Data Science
• Python Basics For Data Science
• Data Analyst vs Data Scientist vs Data Engineer
• Data Science Life-Cycle
• Statistics For Data Science
• Types of Distribution in Statistics
• Bayes Theorem
• Introduction to Artificial Intelligence
• Introduction to Machine Learning
10:54:25 - Machine Learning Basics
• Classification of Machine Learning
• Decision Tree in Machine Learning
• Random Forest Algorithm
• K Means Clustering Algorithm
• Naive Bayes Classifier
• What is Deep Learning?
12:01:22 - Data Science Interview Questions

✅ Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

⏩ Check out the Data Science tutorial videos: https://www.youtube.com/watch?v=X3paOmcrTjQ&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6

#datascience #datasciencecourse #datascienceroadmap #datascientist #datascienceforbeginners #datasciencetools #simplilearn #2025

✅ About Post Graduate Program In Data Science:
This in-depth Data Science program is designed for working professionals, and covers job-critical topics like R, Python programming, Machine Learning techniques, NLP notions, and Data Visualization with Tableau, using an active learning model that includes live sessions from global professionals, practical labs, IBM Hackathons, and corporate ready projects

Key Features
✅
✅
✅ Core curriculum delivered in live online classes by industry experts
✅ Industry-recognized IBM certificates for IBM courses
✅ Engage in live online masterclasses led by Industry Expert, staff, and IBM experts
✅ Exclusive hackathons and Ask Me Anything (AMA) sessions by IBM
✅ Gain exposure to ChatGPT, Gemini, Keras, TensorFlow and other prominent tools
✅ Interactive sessions on the latest AI trends, such as GenAI, prompt engineering, LLMs, and more
✅ 3 capstones and 25+ hands-on projects from various industry domains
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies

Skills Covered
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Model Building and Finetuning
✅ Supervised and Unsupervised Learning
✅ Ensemble Learning
✅ Deep Learning
✅ Data Visualization
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Explainable AI
✅ Machine Learning Algorithms
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
✅ Speech Recognition

Learning Path
✅ Program Induction
✅ Programming Refresher
✅ Data Management using SQL
✅ Python for Data Science (IBM)
✅ Applied Data Science with Python
✅ Machine Learning
✅ Deep Learning Specialization

👉 Enroll Now: https://www.simplilearn.com/iitk-professional-certificate-course-data-analytics?utm_campaign=ruDfwMFpUh0&utm_medium=Description&utm_source=youtube

With this complete Data Science Course For Beginners 2026 FREE, created to guide beginners and career switchers step by step. This video gives you a clear understanding of how data science works in the real world and what skills are needed to succeed in 2025 and beyond.

You’ll begin by learning what data science is and how roles like Data Engineer, Data Scientist, and Data Analyst differ. The course then walks you through a practical data science roadmap, followed by hands-on learning with Python and Pandas for data handling and Matplotlib for data visualization. Next, you’ll explore Exploratory Data Analysis (EDA) and move into core machine learning concepts, including Linear Regression, Logistic Regression, SVM, Decision Trees, and K-Means Clustering. To bridge theory and practice, the video includes a real-world data science project walkthrough.

The course also helps you prepare for jobs with data science interview questions and wraps up with a MCP Server tutorial for practical exposure. Perfect for anyone serious about starting or growing a career in data science.

➡️ Below are the topics covered in Data Science Full Course 2026:
00:00:00 – Introduction to Data Science Full Course 2026
00:01:49 – What is Data Science?
00:06:43 – Data Engineer vs Data Scientist vs Data Analyst
00:15:59 – Roadmap for Data Science
00:24:59 – Python for Data Science
00:27:40 – Pandas for Data Science
01:33:43 – Data Visualization with Matplotlib
02:24:07 – Exploratory Data Analysis (EDA)
03:03:05 – Machine Learning Types
03:14:31 – Linear Regression
06:31:35 – Logistic Regression
07:12:00 – Support Vector Machine (SVM)
07:13:43 – Decision Tree
07:16:13 – Clustering (K-Means)
08:11:30 – Data Science Project Walkthrough
09:32:05 – Data Science Interview Questions
10:37:20 – MCP Server Tutorial

#datasciencefullcourse #datasciencecourse #datasciencetraining #intellipaat

🔥Register for Intellipaat's Premium Data Science Course: https://intellipaat.com/data-s....cientist-course-trai

➡️ About Data Science Course:
This online Data Science course, in collaboration with iHUB, IIT Roorkee & Microsoft, will help you to elevate your Data Science career. In this course, you will master skills like Python, SQL, Statistics, Machine Learning, AI, Power BI & Generative AI, along with real-time industry-oriented projects.

➡️ Key Features:
✅ 50+ Live interactive sessions across 7 months
✅ 218 Hrs Self-paced Videos
✅ 50+ Industry relevant Projects & Quizzes
✅ Live Classes from IIT Faculty & Industry Experts
✅ Certification from iHub IIT Roorkee & Microsoft
✅ 2 Days Campus Immersion at iHub IIT Roorkee

➡️ What’s Covered in This Program?
✅ Linux and Python Fundamentals
✅ Data Wrangling with SQL
✅ Python with Data Science
✅ Linear Algebra and Advanced Statistics
✅ Machine Learning and Prediction Algorithms
✅ Supervised and Unsupervised Learning in ML
✅ Deep Learning with TensorFlow
✅ Generative AI & Prompt Engineering
✅ Deploying Machine Learning Models on Cloud
✅ Data Visualization Tool Power BI

📌 Do subscribe to Intellipaat channel & come across more relevant Tech content: https://goo.gl/hhsGWb

▶️ Intellipaat Achievers Channel: https://www.youtube.com/@intellipaatachievers

📚For more information, please write back to us at sales@intellipaat.com or call us at IND: +91-7022374614 / US : 1-800-216-8930

🔥Data Scientist Masters Program (Discount Code - YTBE15) - https://www.simplilearn.com/data-science-course?utm_campaign=7WRlYJFG7YI&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Microsoft Azure - Data Analyst Course - https://www.simplilearn.com/in/data-analyst-course?utm_campaign=7WRlYJFG7YI&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Microsoft Azure - Data Analyst Course - https://www.simplilearn.com/in/data-analyst-course?utm_campaign=7WRlYJFG7YI&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Data Scientist Masters Program (Discount Code - YTBE15) - https://www.simplilearn.com/data-science-course?utm_campaign=7WRlYJFG7YI&utm_medium=DescriptionFirstFold&utm_source=Youtube

Will cover all the below-given topics required for a complete Data Science Tutorial:
0. Introduction (0:00)
1. Data Science basics (01:28)
2. What is Data Science (05:51)
3. Need for Data Science (06:38)
4. Business intelligence vs Data Science (17:30)
5. Prerequisites for Data Science (22:31)
6. What does a Data Scientist do? (30:23)
7. Demand for Data Scientist (53:03)
8. Linear regression (2:30:10)
9. Decision trees (2:53:39)
10. Logistic regression in R (3:09:12)
11. What is a decision tree? (3:27:04)
12. What is clustering? (4:35:40)
13. Divisive clustering (4:51:14)
14. Support vector machine (5:17:21)
15. K-means clustering 96:44:13)
16. Time series analysis (7:33:05)
17. How to Become a Data Scientist (8:26:54)
18. Job roles in Data Science (8:30:59)
19. Simplilearn certifications in Data Science (8:33:50)
20. Who is a Data Science engineer? (8:34:34)
21. Data Science engineer resume (9:00:04)
22. Data Science interview questions and answers (9:04:42)

Download Datasets: https://drive.google.com/drive..../folders/1oa_hIIb4dn

Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6

#DataScienceWithPython #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #machinelearning

➡️ About Data Science Course in collaboration with IBM

This Data Science course in collaboration with IBM propels your career to become a data scientist. Gain expertise in in-demand skills like Python, SQL, Excel, Machine Learning, Tableau, generative AI, and more. Dive deep into data interpretation nuances, master Machine Learning, and enhance programming skills to elevate your Data Science career.

Key Features
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Masterclasses from IBM experts
✅ Dedicated live sessions by faculty of industry experts
✅ Industry-recognized Data Scientist Master’s certificate from Simplilearn
✅ Industry-recognized IBM certifications for IBM courses
✅ Ask-Me-Anything (AMA) sessions with IBM leadership
✅ Capstone from 3 domains and 25+ projects
✅ Exclusive hackathons conducted by IBM
✅ Lifetime access to self-paced learning content
✅ Program crafted to initiate your journey as a Data Scientist
✅ Integrated labs for hands-on learning experience

Skills Covered
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Explainable AI
✅ Conversational AI
✅ Large Language Models
✅ Model Building and Finetuning
✅ Ensemble Learning
✅ Data Visualization
✅ Database Management

👉 Learn More At: https://www.simplilearn.com/in/data-analyst-course?utm_campaign=DataScienceSep182019&utm_medium=Description&utm_source=youtube

🔥🔥

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚'𝐬 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐌𝐚𝐬𝐭𝐞𝐫𝐬 𝐏𝐫𝐨𝐠𝐫𝐚𝐦 : https://www.edureka.co/masters....-program/data-scient
(𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎)
Data Science Masters Program makes you proficient in tools and systems used by Data Science Professionals. It includes training on Statistics, Data Science, Python, Apache Spark & Scala, Tensorflow and Tableau. The Data Science course curriculum has been determined by extensive research on 5000+ job descriptions across the globe.
📝Feel free to comment your doubts in the comment section below, and we will be happy to answer📝

-------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧---------

🔵 DevOps Online Training:https://bit.ly/3r7xtvQ
🌕 AWS Online Training: https://bit.ly/3r6sawS
🔵 Azure DevOps Online Training:https://bit.ly/3r8shaX
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---------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬---------

🔵 DevOps Engineer Masters Program: https://bit.ly/37p4goY
🌕 Cloud Architect Masters Program: https://bit.ly/35LP0SV
🔵 Data Scientist Masters Program: https://bit.ly/3NULA1q
🌕 Big Data Architect Masters Program:https://bit.ly/38qZTud
🔵 Machine Learning Engineer Masters Program:https://bit.ly/3ueP9rm
🌕 Business Intelligence Masters Program: https://bit.ly/3x9qpT5
🔵 Python Developer Masters Program:https://bit.ly/3j8YYkg
🌕 RPA Developer Masters Program: https://bit.ly/3JgqQ0g
🔵 Web Development Masters Program: https://bit.ly/3KlZJT1
🌕 Computer Science Bootcamp Program : https://bit.ly/3Kg70Uh
🔵 Cyber Security Masters Program: https://bit.ly/3uo98UN
🌕 Full Stack Developer Masters Program : https://bit.ly/3NUlVGb
🔵 Automation Testing Engineer Masters Program : https://bit.ly/3E0rFcZ
🌕 Python Developer Masters Program : https://bit.ly/3j8YYkg
🔵 Azure Cloud Engineer Masters Program: https://bit.ly/3NQb9Ax

--------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐏𝗼𝘀𝘁 𝗚𝗿𝗮𝗱𝘂𝗮𝘁𝗲 𝐂𝐨𝐮𝐫𝐬𝐞𝐬--------
🔵 Artificial and Machine Learning PGD with E & ICT Academy
NIT Warangal: https://bit.ly/3Kji6bb
🌕 Post Graduate Program in DevOps with Purdue University: https://bit.ly/3uoajDH

📢📢 𝐓𝐨𝐩 𝟏𝟎 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐢𝐧 𝟐𝟎𝟐𝟐 𝐒𝐞𝐫𝐢𝐞𝐬 📢📢
⏩𝐓𝐨𝐩 𝟏𝟎 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐢𝐧 𝟐𝟎𝟐𝟮: https://bit.ly/3yhEs7S
⏩𝐓𝐨𝐩 𝟏𝟎 𝐇𝐢𝐠𝐡𝐞𝐬𝐭 𝐏𝐚𝐲𝐢𝐧𝐠 𝐉𝐨𝐛𝐬 𝐅𝐨𝐫 𝟐𝟎𝟐𝟐: https://bit.ly/3HcpPG6
⏩𝐓𝐨𝐩 𝟏𝟎 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐬 𝐟𝐨𝐫 𝟐𝟎𝟐𝟐: https://bit.ly/3FW6F69
⏩𝐓𝐨𝐩 𝟏𝟎 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 𝟐𝟎𝟐𝟐: https://bit.ly/3gH57mr

📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
📌𝐓𝐰𝐢𝐭𝐭𝐞𝐫: https://twitter.com/edurekain
📌𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧: https://www.linkedin.com/company/edureka
📌𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦: https://www.instagram.com/edureka_learning/
📌𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤: https://www.facebook.com/edurekaIN/
📌𝐒𝐥𝐢𝐝𝐞𝐒𝐡𝐚𝐫𝐞: https://www.slideshare.net/EdurekaIN
📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/


Is there any eligibility criteria for this program?
A potential candidate must have one of the following prerequisites: Degrees like BCA, MCA, and B.Tech or Programming experience Should have studied PCM in 10+2

🔥Edureka Python for Data Science Certification Training (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎"): https://www.edureka.co/data-sc....ience-python-certifi
This Edureka video on the 'Python For Data Science Full Course' will help you learn Python for Data Science including all the relevant libraries. Following are the topics discussed in this Python for Data Science tutorial:

00:00 Agenda
02:37 Introduction To Data Science
03:03 Need for Data Science
06:05 What is Data Science
10:56 Data Science Life Cycle
26:50 Jupyter Notebook Tutorial
48:34 Statistics For Data Science
02:14:32 Python Libraries For Data Science
02:14:25 Python Numpy
02:44:42 Python Pandas
03:18:24 Python Scipy
03:36:21 Python Matplotlib
04:04:19 Python Seaborn
04:22:57 Machine Learning With Python
04:33:47 Maths For Machine Learning
05:32:40 Machine Learning Algorithms
05:41:36 Classification In Machine Learning
06:14:07 Linear Regression In Machine Learning
06:41:59 Logistic Regression In Machine Learning
7:33:44 Deep Learning With Python
07:40:10 Keras Tutorial
08:06:14 TensorFlow Tutorial
08:52:35 Pyspark Tutorial

🔹 Edureka Community: https://bit.ly/EdurekaCommunity
🔹 Python Data Science Tutorial Playlist: https://goo.gl/WsBpKe
🔹 Python Data Science Blog Series: http://bit.ly/2sqmP4s

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

🔵 Python Online Training: http://bit.ly/3Oubt8M
🔵 Data Science Online Training: http://bit.ly/3V3nLrc

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬

🔵 Data Scientist Masters Program: http://bit.ly/3tUAOiT
🔵 Python Developer Masters Program: http://bit.ly/3EV6kDv

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐬

🔵 Advanced Certificate Program in Data Science with E&ICT Academy, IIT Guwahati: http://bit.ly/3V7ffrh

🌕 Artificial and Machine Learning PGD with E&ICT Academy
NIT Warangal: http://bit.ly/3OuZ3xs

🔴 Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV

---------------------------------
Edureka Community: https://bit.ly/EdurekaCommunity
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
SlideShare: https://www.slideshare.net/EdurekaIN

#edureka #PythonEdureka #pythonfordatasciencefullcourse #pythonprojects #pythontutorial #PythonTraining

About the course

Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. For over a decade, Python has been used in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing.

Edureka's Python Certification Training not only focuses on the fundamentals of Python, Statistics and Machine Learning but also helps one gain expertise in applied Data Science at scale using Python. The training is a step by step guide to Python and Data Science with extensive hands-on. The course is packed with several activity problems and assignments and scenarios that help you gain practical experience in addressing predictive modeling problems that would either require Machine Learning using Python. Starting from basics of Statistics such as mean, median and mode to exploring features such as Data Analysis, Regression, Classification, Clustering, Naive Bayes, Cross-Validation, Label Encoding, Random Forests, Decision Trees and Support Vector Machines with a supporting example and exercise help you get into the weeds.

Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to train your machine based on real-life scenarios using Machine Learning Algorithms.

Edureka’s Python course will also cover both basic and advanced concepts of Python like writing Python scripts, sequence and file operations in Python. You will use libraries like pandas, numpy, matplotlib, scikit, and master concepts like Python machine learning, scripts, and sequence.
---------------------------------
Why learn Python?

It's continued to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging programs is a breeze in Python with its built-in debugger.

---------------------------------
For more information, please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775

🔥 Intellipaat's Data Science Course: https://intellipaat.com/data-s....cientist-course-trai

🔥 Free Self-Paced Data Science Study Plan for Beginners: https://linktw.in/nSVhcp

#DataScience #DataScientist #DataScienceCourse #DataScienceCoursesFree

The Data Science Full Course for Beginners by Intellipaat is designed in collaboration with real-time industry experts to provide a comprehensive learning experience. This Data Science Training program has been meticulously crafted based on a thorough analysis of data scientist job descriptions for 2024, ensuring that you acquire the skills necessary for an entry-level data scientist role. Throughout this Data Science Tutorial for Beginners, you'll explore fundamental topics such as what data science is, how to become a data scientist in 2024, machine learning for data science, and various data science algorithms. Additionally, the course offers insights into common data science interview questions for 2024 and features a stellar data science project that will help set you apart from the competition.

📖Below are the concepts covered in this 'Data Science Full Course' video:
00:00:00 - Introduction to Data Science Course
00:02:50 - What is Data Science?
00:09:30 - How to Become a Data Scientist in 2024?
00:20:15 - What Does a Data Scientist Do?
00:23:10 - How to Master Data Science
00:36:50 - Machine Learning with Python
00:51:40 - Machine Learning Basics
01:14:00 - ML Myths
01:31:14 - TYPES OF ML
01:54:00 - Classification Algorithms
02:07:07 - What is Regression?
02:21:06 - Types of Regression
02:28:22 - What is Linear Regression?
03:24:37 - What is Logistic Regression?
03:43:00 - Linear Regression Hands-On
04:50:00 - Logistic Regression Hands-On
07:20:00 -Decision Tree Algorithm
08:53:00 - Random Forest Algorithm in Machine Learning
10:20:44 - Data Science Project (Book Recommendation System)
11:00:00 - Data Science Interview Questions and Answers

✅ What exactly is data science course?
A Data Science Course is a complete learning resource that would enable you to master the data science discipline. You will get to learn about the fundamentals of data science such as Machine Learning, Multiple data science algorithms, projects, etc.

👉🏼In this Free Data Science courses video, you will undergo 4+ Data Science Courses along with multiple Quizes and industry-oriented project.
Course 1: Introduction to Data Science
Course 2: Machine Learning with Python
Course 3: Supervised and Unsupervised Learning in ML
Course 4: Building Robust Data Science Project

➡️ About the Course
This instructor-led Data Science Training, in association with iHUB, IIT Roorkee, will help you master Data Science & AI. The training covers Python, SQL, Statistics, Machine Learning, AI, etc, along with work on real-time projects.

➡️Who should take this course?
☑️Information Architects and Statisticians
☑️Developers looking to master Machine Learning and Predictive Analytics
☑️Big Data, Business Analysis, Business Intelligence, and Software Engineering Professionals


➡️Key Features - (Course Features)
👉🏼50+ Live sessions across 7 months
👉🏼218 Hrs Self-paced Videos
👉🏼200 Hrs Project & Exercises
👉🏼Learn from IIT Roorkee Faculty and Industry Practitioners
👉🏼1:1 with Industry Mentors and 24*7 Support
👉🏼Campus Immersion at IIT Roorkee

➡️What’s Covered in This Program? -
✅Preparatory Session - Linux and Python
✅Data Wrangling with SQL
✅Python with Data Science
✅Linear Algebra and Advanced Statistics
✅Machine Learning
✅Performance Metrics
✅Deep Learning Using TensorFlow
✅Data Science Capstone Project
✅Business Case Studies

📌Do subscribe to Intellipaat channel & come across more relevant Tech content: https://www.youtube.com/@Intellipaat
📌Intellipaat Achievers Channel: https://www.youtube.com/@intellipaatachievers

More Intellipaat Advanced Certifications -
🌕 Advanced Certification in Cloud Computing: https://intellipaat.com/advanc....ed-certification-in-
🌕 Advanced Certification in Data Science: https://intellipaat.com/advanc....ed-certification-in-
🌕 Advanced Certification in Full Stack Web Development: https://intellipaat.com/web-de....velopment-certificat
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Here is Data Science full course to help you understand the DS in depth. This session will help you understand the concepts around Data Science and how to go about writing a research paper. Check out our FREE masterclasses by Industry Leading experts now: https://www.scaler.com/events?utm_source=osocial&utm_medium=googleyoutube&utm_campaign=brand_scaler_events_osocial_googleyoutube_data-science-tutorial-2023&utm_content=description

What is Data Science?

Data science is a field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured Data, and apply insights from data across a broad range of application domains. Data science combines the scientific method, math and statistics, specialised programming, and advanced analytics, to uncover and explain the insights buried in data.

What is Machine Learning?
Machine learning (ML) is the study of computer algorithms that can improve automatically through experience and by the use of data .It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so.

Busting Data Science Myths:

It’s easier now than ever before for ideas to spread around the world, including through fact-based communities like the one inhabited by data scientists. However, that doesn’t necessarily mean that every data science “fact” we hear is actually truthful.

In fact, some commonly known “facts” are little more than hearsay, misinterpretations, or, at worst, outright myths.

Python Programming Language:
Python is the most widely used data science programming language in the world today. It is an open-source, easy-to-use language that has been around since the year 1991. This general-purpose and dynamic language is inherently object-oriented. It also supports multiple paradigms, from functional to structured and procedural programming. Therefore, it is one of the most popular languages for data science as well. With less than 1000 iterations, it is faster and a better option for data manipulations.

What is A/B testing?
A/B testing, also known as split testing, refers to a randomised experimentation process wherein two or more versions of a variable (web page, page element, etc.) are shown to different segments of website visitors at the same time to determine which version leaves the maximum impact and drive business metrics. Essentially, A/B testing eliminates all the guesswork out of website optimization and enables experience optimisers to make data-backed decisions.

What is the Confusion Matrix?
A confusion matrix is a tool for predictive analysis. It’s a table that compares predicted values with actual values. In the machine learning context, a confusion matrix is a metric used to quantify the performance of a machine learning classifier. The confusion matrix is used when there are two or more classes as the output of the classifier.


0:00 - Introduction
1:25 - Highest Paying Data Job Roles
26:15 - Data Science Myths Busted
40:12 - Data Scientist vs ML Engineer
49:20 - What is Data Science?
1:43:43 - Data Science & AI for beginners
2:06:22 - Python for Data Science
2:57:54 - Data Science with Python and R
3:52:22 - A/B Testing Basics Explained
4:11:20 - Confusion Matrix
4:29:48 - Principle Component Analysis
4:45:07 - Data Science Interview Questions
7:13:03 - Research Papers on Data Science & Machine Learning

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Kickstart your Data Science career in 2025 with this complete step-by-step course by Intellipaat perfect for beginners and professionals looking to upskill. In this full video, you’ll learn everything from Python to Machine Learning, along with real-world projects and interview prep.

We’ll start with the basics of Data Science, understand the roles of Data Engineer, Data Scientist, and Data Analyst, and explore the career roadmap for 2025. Then, dive into hands-on learning with Python, Pandas, Matplotlib, and EDA, followed by Machine Learning algorithms like Linear & Logistic Regression, SVM, Decision Trees, and K-Means Clustering. Finally, watch a complete Data Science project walkthrough, get interview-ready, and learn MCP Server implementation to boost your practical knowledge.

Below are the topics covered in Data Science Full Course 2025:
00:00:00 - Introduction to Data Science Full Course 2025
00:01:49– What is Data Science?
00:06:43 – Data Engineer vs Data Scientist vs Data Analyst
00:15:59 - Roadmap for Data Science
00:24:59 – Python for Data Science
00:27:40 – Pandas for Data Science
01:33:43 – Data Visualization with Matplotlib
02:24:07 – Exploratory Data Analysis (EDA)
03:03:05 – Machine Learning Types
03:14:31 – Linear Regression
06:31:35 – Logistic Regression
07:12:00 – Support Vector Machine (SVM)
07:13:43 – Decision Tree
07:16:13 – Clustering (K-Means)
08:11:30 – Data Science Project Walkthrough
09:32:05 – Data Science Interview Questions
10:37:20 – MCP Server Tutorial

#datasciencefullcourse #datasciencecourse #datasciencetraining #intellipaat

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➡️ About Data Science Course:
This online Data Science course, in collaboration with iHUB, IIT Roorkee & Microsoft, will help you to elevate your Data Science career. In this course, you will master skills like Python, SQL, Statistics, Machine Learning, AI, Power BI & Generative AI, along with real-time industry-oriented projects.

➡️ Key Features:
✅ 50+ Live interactive sessions across 7 months
✅ 218 Hrs Self-paced Videos
✅ 50+ Industry relevant Projects & Quizzes
✅ Live Classes from IIT Faculty & Industry Experts
✅ Certification from iHub IIT Roorkee & Microsoft
✅ 2 Days Campus Immersion at iHub IIT Roorkee

➡️ What’s Covered in This Program?
✅ Linux and Python Fundamentals
✅ Data Wrangling with SQL
✅ Python with Data Science
✅ Linear Algebra and Advanced Statistics
✅ Machine Learning and Prediction Algorithms
✅ Supervised and Unsupervised Learning in ML
✅ Deep Learning with TensorFlow
✅ Generative AI & Prompt Engineering
✅ Deploying Machine Learning Models on Cloud
✅ Data Visualization Tool Power BI

📌 Do subscribe to Intellipaat channel & come across more relevant Tech content: https://goo.gl/hhsGWb

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📚For more information, please write back to us at sales@intellipaat.com or call us at IND: +91-7022374614 / US : 1-800-216-8930

🔥Data Scientist Masters Program (Discount Code - YTBE15) - https://www.simplilearn.com/big-data-and-analytics/senior-data-scientist-masters-program-training?utm_campaign=yoy-2kwzKd0&utm_medium=DescriptionFirstFold&utm_source=Youtube
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This Data Science Full Course 2026 by Simplilearn, begins with an introduction to data science, building a strong foundation in the field. You’ll then dive into probability and statistics and the essential mathematics for machine learning, which form the backbone of data-driven problem-solving. The program continues with a detailed roadmap to data science, guiding you through the most in-demand skills, tools, and frameworks needed for career growth. From there, you’ll explore key machine learning algorithms, including classification, decision trees, random forests, K-means clustering, and Naive Bayes, before moving into deep learning concepts such as neural networks and model optimization. You’ll also gain hands-on experience with Python, NumPy, Pandas, Matplotlib, and Scikit-learn to analyze and visualize data effectively. By the end of this course, you’ll not only master the complete lifecycle of a data science project—from data collection and cleaning to model deployment, but also develop the confidence to tackle real-world case studies. Finally, the course concludes with data science interview questions and answers designed to prepare you for top-tier roles in analytics and AI-driven industries.

Following are the topics covered in Data Science Full Course 2026:

00:00:00 - Data Science Full Course 2026
00:02:08 - Introduction to Data Science
03:07:51 - Probability and Statistics
03:54:10 - Mathematics for Machine Learning
05:44:34 - Roadmap to Data Science
05:53:46 - Machine Learning Algorithms
- Classification of Machine Learning
- Decision Tree in Machine Learning
- Random Forest Algorithm
- K Means Clustering Algorithm
- Naive Bayes Classifier
- What Is Deep Learning?
09:10:45 - Data Science Interview Questions and Answers

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⏩ Check out the Data Science tutorial videos: https://www.youtube.com/watch?v=X3paOmcrTjQ&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6

#datascience #datasciencecourse #datascienceroadmap #datascientist #datascienceforbeginners #datasciencetools #simplilearn #2026

✅ About Post Graduate Program In Data Science:
This in-depth Data Science program is designed for working professionals, and covers job-critical topics like R, Python programming, Machine Learning techniques, NLP notions, and Data Visualization with Tableau, using an active learning model that includes live sessions from global professionals, practical labs, IBM Hackathons, and corporate ready projects

Key Features
✅
✅
✅ Core curriculum delivered in live online classes by industry experts
✅ Industry-recognized IBM certificates for IBM courses
✅ Engage in live online masterclasses led by Industry Expert, staff, and IBM experts
✅ Exclusive hackathons and Ask Me Anything (AMA) sessions by IBM
✅ Gain exposure to ChatGPT, Gemini, Keras, TensorFlow and other prominent tools
✅ Interactive sessions on the latest AI trends, such as GenAI, prompt engineering, LLMs, and more
✅ 3 capstones and 25+ hands-on projects from various industry domains
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies

Skills Covered
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Model Building and Finetuning
✅ Supervised and Unsupervised Learning
✅ Ensemble Learning
✅ Deep Learning
✅ Data Visualization
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Explainable AI
✅ Machine Learning Algorithms
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
✅ Speech Recognition

Learning Path
✅ Program Induction
✅ Programming Refresher
✅ Data Management using SQL
✅ Python for Data Science (IBM)
✅ Applied Data Science with Python
✅ Machine Learning
✅ Deep Learning Specialization

👉 Enroll Now: https://www.simplilearn.com/in/data-analyst-course?utm_campaign=yoy-2kwzKd0&utm_medium=Description&utm_source=youtube

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This What is Data Science Video will give you an idea of a life of Data Scientist. This Data Science for Beginners video will also explain the steps involved in the Data Science project, roles & salary offered to a Data Scientist. Data Science is basically dealing with unstructured and structured data. Data Science is a field that comprises of everything that is related to data cleansing, preparation, and data analysis.

Below topics are explained in this Data Science tutorial:

00:00 Introduction
00:10 Life of a Data Scientist
Steps in Data Science project
00:21 Understanding the business problem
00:37 Data acquisition
00:51 Data preparation
01:29 Exploratory data analysis
01:52 Data modeling
02:20 Visualization and communication
02:43 Deploy & maintenance
03:11 Roles offered to a Data Scientist
03:53 Salary of a Data Scientist

To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/S....implilearn?sub_confi

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Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6

#DataScience #WhatIsDataScience #DataScienceForBeginners #DataScientist #DataScienceTutorial #DataScienceWithPython #DataScienceWithR #DataScienceCourse #BusinessAnalytics #DataScience101 #MachineLearning

➡️ About Data Science Course in collaboration with IBM

This Data Science course in collaboration with IBM propels your career to become a data scientist. Gain expertise in in-demand skills like Python, SQL, Excel, Machine Learning, Tableau, generative AI, and more. Dive deep into data interpretation nuances, master Machine Learning, and enhance programming skills to elevate your Data Science career.

Key Features
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Masterclasses from IBM experts
✅ Dedicated live sessions by faculty of industry experts
✅ Industry-recognized Data Scientist Master’s certificate from Simplilearn
✅ Industry-recognized IBM certifications for IBM courses
✅ Ask-Me-Anything (AMA) sessions with IBM leadership
✅ Capstone from 3 domains and 25+ projects
✅ Exclusive hackathons conducted by IBM
✅ Lifetime access to self-paced learning content
✅ Program crafted to initiate your journey as a Data Scientist
✅ Integrated labs for hands-on learning experience

Skills Covered
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Explainable AI
✅ Conversational AI
✅ Large Language Models
✅ Model Building and Finetuning
✅ Ensemble Learning
✅ Data Visualization
✅ Database Management

👉 Learn More At: https://www.simplilearn.com/in/data-analyst-course?utm_campaign=DataScienceScribe&utm_medium=Description&utm_source=youtube

🔥🔥

Welcome to the Intellipaat's Data Science Full Course 2025 your complete roadmap to becoming a Data Scientist from scratch! Whether you’re a beginner or an upskiller, this one video covers everything you need to master Python, Machine Learning, EDA, and real-world projects all in one place.

In this course, you’ll learn what Data Science really is, explore the differences between Data Engineer, Data Analyst, and Data Scientist, and get a clear career roadmap for 2025. Then, dive deep into Python, Pandas, Data Visualization (Matplotlib), Machine Learning models, and even a complete Data Science Project Walkthrough. Plus, we’ll end with real interview questions and a hands-on MCP Server tutorial to help you stand out in job interviews. If you’re serious about starting your Data Science career, don’t skip this video it’s the only guide you need for 2025!

Below are the topics covered in Data Science Full Course 2025:
00:00:00 - Introduction to Data Science Full Course 2025
00:01:49– What is Data Science?
00:06:43 – Data Engineer vs Data Scientist vs Data Analyst
00:15:59 - Roadmap for Data Science
00:24:59 – Python for Data Science
00:27:40 – Pandas for Data Science
01:33:43 – Data Visualization with Matplotlib
02:24:07 – Exploratory Data Analysis (EDA)
03:03:05 – Machine Learning Types
03:14:31 – Linear Regression
06:31:35 – Logistic Regression
07:12:00 – Support Vector Machine (SVM)
07:13:43 – Decision Tree
07:16:13 – Clustering (K-Means)
08:11:30 – Data Science Project Walkthrough
09:32:05 – Data Science Interview Questions
10:37:20 – MCP Server Tutorial

#datasciencefullcourse #datasciencecourse #datasciencetraining #intellipaat

🔥Register for Intellipaat's Premium Data Science Course: https://intellipaat.com/data-s....cientist-course-trai

➡️ About Data Science Course:
This online Data Science course, in collaboration with iHUB, IIT Roorkee & Microsoft, will help you to elevate your Data Science career. In this course, you will master skills like Python, SQL, Statistics, Machine Learning, AI, Power BI & Generative AI, along with real-time industry-oriented projects.

➡️ Key Features:
✅ 50+ Live interactive sessions across 7 months
✅ 218 Hrs Self-paced Videos
✅ 50+ Industry relevant Projects & Quizzes
✅ Live Classes from IIT Faculty & Industry Experts
✅ Certification from iHub IIT Roorkee & Microsoft
✅ 2 Days Campus Immersion at iHub IIT Roorkee

➡️ What’s Covered in This Program?
✅ Linux and Python Fundamentals
✅ Data Wrangling with SQL
✅ Python with Data Science
✅ Linear Algebra and Advanced Statistics
✅ Machine Learning and Prediction Algorithms
✅ Supervised and Unsupervised Learning in ML
✅ Deep Learning with TensorFlow
✅ Generative AI & Prompt Engineering
✅ Deploying Machine Learning Models on Cloud
✅ Data Visualization Tool Power BI

📌 Do subscribe to Intellipaat channel & come across more relevant Tech content: https://goo.gl/hhsGWb

▶️ Intellipaat Achievers Channel: https://www.youtube.com/@intellipaatachievers

📚For more information, please write back to us at sales@intellipaat.com or call us at IND: +91-7022374614 / US : 1-800-216-8930

🔥Discover SKillUP free online certification programs – https://www.simplilearn.com/skillup-free-online-courses?utm_campaign=18FebSKillupYT&utm_medium=DescriptionFF&utm_source=youtube

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In this video on R for Data Science Full Course, we’ll start by learning data science from an animated video. You will then learn the essential concepts in data science and understand the important packages in R for data science. You will look at some of the widely used data science algorithms such as Linear regression, logistic regression, decision trees, and random forest, including time-series analysis. Finally, you will get an idea about the Salary structure, Skills, Jobs, and resume of a data scientist.

Dataset Link - https://drive.google.com/drive..../folders/1Wn2TRSbM2C

00:00:00 Data science in 5 min
00:05:23 Data science concept
00:17:40 Data science package in R
01:18:51 Linear Regression in R
01:47:07 Use Case :Linear Regression
02:04:31 Logistic Regression in R
02:22:37 Decision tree in R
03:22:03 Random forest in R
04:02:10 What is clustering
04:43:54 Time series analysis
05:54:16 Salary, Skills, and resume

✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

⏩ Check out the Data Science training videos: https://bit.ly/3fKucdD

#RForDataScience #DataScienceWithR #DataScienceWithRFullCourse #DataScienceWithRTutorial #DataScienceFullCourse #DataScienceTutorial #DataScience #Simplilearn

➡️ About Data Science Course in collaboration with IBM
This Data Science course in collaboration with IBM propels your career to become a data scientist. Gain expertise in in-demand skills like Python, SQL, Excel, Machine Learning, Tableau, generative AI, and more. Dive deep into data interpretation nuances, master Machine Learning, and enhance programming skills to elevate your Data Science career.

✅ Key Features
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Masterclasses from IBM experts
- Dedicated live sessions by faculty of industry experts
- Industry-recognized Data Scientist Master’s certificate from Simplilearn
- Industry-recognized IBM certifications for IBM courses
- Ask-Me-Anything (AMA) sessions with IBM leadership
- Capstone from 3 domains and 25+ projects
- Exclusive hackathons conducted by IBM
- Lifetime access to self-paced learning content
- Program crafted to initiate your journey as a Data Scientist
- Integrated labs for hands-on learning experience

✅ Skills Covered
- Generative AI
- Prompt Engineering
- ChatGPT
- Exploratory Data Analysis
- Descriptive Statistics
- Inferential Statistics
- Explainable AI
- Conversational AI
- Large Language Models
- Model Building and Finetuning
- Ensemble Learning
- Data Visualization
- Database Management

Learn more at: https://www.simplilearn.com/data-science-course?utm_campaign=RForDSFullCourseDec172020&utm_medium=Description&utm_source=youtube

🔥Data Scientist Masters Program (Discount Code - YTBE15) - https://www.simplilearn.com/data-science-course?utm_campaign=QjqJS0yb8YM&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Microsoft Azure - Data Analyst Course - https://www.simplilearn.com/in/data-analyst-course?utm_campaign=QjqJS0yb8YM&utm_medium=DescriptionFirstFold&utm_source=Youtube
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This Data Science Full Course 2026 by Simplilearn provides a structured learning path for mastering data science concepts. It starts with an introduction to data science, followed by a roadmap to becoming a data scientist. Learners will explore deep learning, probability, and statistics, which form the foundation of data science. The course then introduces Large Language Models (LLMs), benchmarking techniques, and the key differences between AI, ML, and DL. It also covers AI bias, OpenAI ChatGPT, and Generative AI tools for job interviews. Practical aspects are included with beginner-friendly machine learning projects and an overview of Mistral AI. Finally, the course concludes with data science interview questions, ensuring learners are well-prepared for real-world applications and job opportunities.

Following are the topics covered in Data Science Full Course 2026:

00:00:00 - Introduction to Data Science Full Course
00:00:00 - Introduction to Data Science Full Course 2026
00:04:21 - What is Data Science
00:10:31 - Data science course unboxing
00:19:43 - Roadmap to Data Science
01:06:02 - Probability and Statistics
06:57:34 - Data Science basics
06:58:58 - Introduction to LLM
08:07:47 - RAG for Beginners
11:24:46 - Machine Learning Basics
- Data Science Interview Questions

✅ Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

⏩ Check out the Data Science tutorial videos: https://www.youtube.com/watch?v=X3paOmcrTjQ&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6

#datascience #datasciencecourse #datascienceroadmap #datascientist #datascienceforbeginners #datasciencetools #simplilearn #2026

✅ About Post Graduate Program In Data Science:
This in-depth Data Science program is designed for working professionals, and covers job-critical topics like R, Python programming, Machine Learning techniques, NLP notions, and Data Visualization with Tableau, using an active learning model that includes live sessions from global professionals, practical labs, IBM Hackathons, and corporate ready projects

Key Features
✅
✅
✅ Core curriculum delivered in live online classes by industry experts
✅ Industry-recognized IBM certificates for IBM courses
✅ Engage in live online masterclasses led by Industry Expert, staff, and IBM experts
✅ Exclusive hackathons and Ask Me Anything (AMA) sessions by IBM
✅ Gain exposure to ChatGPT, Gemini, Keras, TensorFlow and other prominent tools
✅ Interactive sessions on the latest AI trends, such as GenAI, prompt engineering, LLMs, and more
✅ 3 capstones and 25+ hands-on projects from various industry domains
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies

Skills Covered
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Model Building and Finetuning
✅ Supervised and Unsupervised Learning
✅ Ensemble Learning
✅ Deep Learning
✅ Data Visualization
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Explainable AI
✅ Machine Learning Algorithms
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
✅ Speech Recognition

Learning Path
✅ Program Induction
✅ Programming Refresher
✅ Data Management using SQL
✅ Python for Data Science (IBM)
✅ Applied Data Science with Python
✅ Machine Learning
✅ Deep Learning Specialization

👉 Enroll Now: https://www.simplilearn.com/in/data-analyst-course?utm_campaign=QjqJS0yb8YM&utm_medium=Description&utm_source=youtube

Want a career in Data Science? Start here → https://ibm.biz/BdK65F
Data Science touches almost every operation of a business. See how → https://ibm.biz/BdPEfu

Data Science is the convergence of computer science, mathematics, and business expertise and helps entrepreneurs predict, diagnose, and solve their problems. Luv Aggarwal, a Data Solution Engineer at IBM, goes through the basics and explains how the discipline deploys data mining, data cleaning, machine learning and a variety of advanced analytics to yield actionable insights that will provide a roadmap for growth.

AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdK65E

#DataScience #BusinessSolutions #Lightboard #IBM #ComputerScience #Data #MachineLearning

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Below topics are explained in this Python for Data Science video:
00:00:00 Data Science Basics
00:05:38 Data Science libraries
00:51:05 Mathematics for Data Science
03:06:55 Data Science algorithms using python
06:24:35 Regularization, PCA, Cost Functions
10:47:23 Who is a Data Scientist

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➡️ About Data Science Course in collaboration with IBM

This Data Science course in collaboration with IBM propels your career to become a data scientist. Gain expertise in in-demand skills like Python, SQL, Excel, Machine Learning, Tableau, generative AI, and more. Dive deep into data interpretation nuances, master Machine Learning, and enhance programming skills to elevate your Data Science career.

Key Features
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Masterclasses from IBM experts
✅ Dedicated live sessions by faculty of industry experts
✅ Industry-recognized Data Scientist Master’s certificate from Simplilearn
✅ Industry-recognized IBM certifications for IBM courses
✅ Ask-Me-Anything (AMA) sessions with IBM leadership
✅ Capstone from 3 domains and 25+ projects
✅ Exclusive hackathons conducted by IBM
✅ Lifetime access to self-paced learning content
✅ Program crafted to initiate your journey as a Data Scientist
✅ Integrated labs for hands-on learning experience

Skills Covered
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Explainable AI
✅ Conversational AI
✅ Large Language Models
✅ Model Building and Finetuning
✅ Ensemble Learning
✅ Data Visualization
✅ Database Management

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Data Science Full Course for Beginners by simplilearn is curated in collaboration with real-time industry experts. This Data Science Tutorial will help you learn data science in 12 hours. The data science course will cover the major data science concepts like Artificial Intelligence, Machine Learning, Deep Learning, Supervised Learning, Unsupervised Learning, Reinforcement learning and much more. this full course covers the following

00:00:00 Data Science Full Course
00:03:24 Introduction to Data Science
01:00:16 Data Analyst vs Data Scientist vs Data Engineer
01:07:49 Data Science Life Cycle
01:24:14 Statistic for Data Science
01:44:32 Types of Distribution in Statistics
02:09:17 Bayes Theorem
02:14:18 Introduction to Artificial Intelligence
02:18:07 Introduction to Machine Learning
02:26:49 Types of Machine Learning
02:44:14 Supervised Vs Unsupervised vs Reinforced Learning
03:21:14 Regression Analysis
03:27:35 Linear Regression
04:02:20 Logistic Regression
04:38:50 Linear vs Logistic Regression
05:04:26 Classification of Machine Learning
05:47:45 Decision Tree in Machine Learning
06:39:31 Random Forest Algorithm
07:24:11 K Means Clustering Algorithm
08:14:10 Naive Bayes Classifier
08:57:28 What is Deep Learning?
09:35:04 Natural Language Processing
09:39:59 Python Libraries
09:55:56 Data Visualization - Tableau
10:42:34 Data Science Engineer Resume
10:47:30 Data Science Interview Questions

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#DataScienceFullCourse2023 #DataScience #IntroductionToDataScience #LearnDataScience #DataScienceFullCourseForBeginners #WhatIsDataScience #DataScienceCareers #DataScience #LearnDataScience #2026 #DataScience #DataScienceTutorial #DataScienceCourse #Simplilearn

➡️ About Data Science Course in collaboration with IBM

This Data Science course in collaboration with IBM propels your career to become a data scientist. Gain expertise in in-demand skills like Python, SQL, Excel, Machine Learning, Tableau, generative AI, and more. Dive deep into data interpretation nuances, master Machine Learning, and enhance programming skills to elevate your Data Science career.

Key Features
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Masterclasses from IBM experts
✅ Dedicated live sessions by faculty of industry experts
✅ Industry-recognized Data Scientist Master’s certificate from Simplilearn
✅ Industry-recognized IBM certifications for IBM courses
✅ Ask-Me-Anything (AMA) sessions with IBM leadership
✅ Capstone from 3 domains and 25+ projects
✅ Exclusive hackathons conducted by IBM
✅ Lifetime access to self-paced learning content
✅ Program crafted to initiate your journey as a Data Scientist
✅ Integrated labs for hands-on learning experience

Skills Covered
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Explainable AI
✅ Conversational AI
✅ Large Language Models
✅ Model Building and Finetuning
✅ Ensemble Learning
✅ Data Visualization
✅ Database Management

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Get started with data science using Python! This course covers essential tools like Pandas and NumPy, plus data visualization, cleaning, and machine learning techniques. Perfect for beginners, you'll gain the skills to analyze and interpret data effectively.

YouTube Channel: https://www.youtube.com/@ThePyCoach
Source Code & Datasets: https://github.com/thepycoach/....python-for-data-scie
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Course in Spanish: https://youtu.be/Rgag-Clu5L4

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⭐️ Contents ⭐️
⌨️ (0:00:00) Installation and Setup
⌨️ (0:27:23) Python Basics
⌨️ (1:41:41) Introduction to Pandas and Numpy
⌨️ (3:26:15) Project #1 - Web Scraping with Pandas
⌨️ (4:05:36) Filtering Data
⌨️ (5:34:46) Data Extraction
⌨️ (7:31:57) Reshaping and Pivoting Dataframes
⌨️ (7:50:59) Project #2: Making Data Visualizations
⌨️ (8:56:39) GroupBy and Aggregate Function
⌨️ (10:07:41) Merging and Concatenating Dataframes
⌨️ (11:49:12) Regular Expressions
⌨️ (12:45:45) Project #3: Data Cleaning with Pandas
⌨️ (14:17:45) Machine Learning with Python
⌨️ (14:43:45) Project #4: Text Classification with scikit-learn

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In this video on the Data Science course, you will learn what is Data Science, Types of Data Analytics, Life Cycle of Data Science, Data Visualisation, How to Create and Test a Model, Statistics for Data Science, and Probability, R programming, Machine learning, Numpy, Hands-on demo on Book Recommendation System, Skills Required to Become a Data Scientist, Trends in Data Science Science, Data Science vs Data Analytics, Data Science Interview Questions.
This is a must-watch session for everyone who wishes to learn data science and make a career in it.

#DataScienceCourse #DataScienceFullCourse #DataScientistForBeginners #DataScienceTutorialForBeginners #DataScientistCourse #DataScience #Intellipaat
00:00 - Introduction
10:15 - How machine learning works?
16:40 - Data
21:15 - Need of data science
49:39 - What is data science?
55:08 - Types of data analytics
01:01:33 - Life cycle of data science
01:22:37 - Data science process
01:29:58 - Data Cleaning
01:30:40 - Data Visualization
01:34:33 - Creating a model
01:51:02 - Converting data into useful information
02:02:02 - Descriptive Statistics
02:25:51 - Basic definitions
02:40:31 - What is probability?
02:59:45 - Variables in R
03:29:01 - Data types in R
03:56:33 - Objects in R
04:35:03 - Quiz
04:46:03 - Hands-on
05:08:01 - Dream Job
05:37:20 - Machine learning types
05:53:50 - What is regression?
06:03:00 - Types of regression
06:18:36 - Understanding linear regression
06:31:24 - Linear regression(Recap)
06:35:04 - What is logistic regression?
06:57:58 - What is classification?
07:08:58 - What is scikit learn?
07:16:18 - Steps in building a classifier
07:27:18 - What is NumPy?
07:38:17 - Initializing Numpy Array
07:54:49 - Find the data type of the array
08:19:32 - Numpy indexing and scaling
08:35:06 - Characteristics of Scipy
09:04:21 - Tasks to be performed
🔵 Read complete Data Science tutorial here: https://intellipaat.com/blog/t....utorial/data-science

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----------------------------
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This Data Science Full Course 2025 by Intellipaat is a complete step-by-step learning path for anyone aspiring to build a successful career in data science. The course begins with the fundamentals, explaining what data science is, the roles of data engineers, data scientists, and data analysts, and a clear roadmap to get started. You will then move into Python for Data Science, mastering Pandas for data manipulation and Matplotlib for data visualization. The training dives into exploratory data analysis (EDA) and introduces machine learning concepts, including supervised and unsupervised learning techniques. Core algorithms such as linear regression, logistic regression, support vector machines (SVM), decision trees, and clustering with K-Means are explained with practical examples.

A full project walkthrough gives you hands-on exposure to applying data science in real-world scenarios. To prepare you for career success, the course also covers frequently asked interview questions and includes an MCP server tutorial. Whether you’re a beginner or upskilling for 2025, this free data science tutorial equips you with essential tools, techniques, and industry insights.

Below are the topics covered in Data Science Full Course 2025:
00:00:00 - Introduction to Data Science Full Course 2025
00:01:31 – What is Data Science?
00:06:23 – Data Engineer vs Data Scientist vs Data Analyst
00:15:40 - Roadmap for Data Science
00:24:40 – Python for Data Science
00:27:20 – Pandas for Data Science
01:33:23 – Data Visualization with Matplotlib
02:23:47 – Exploratory Data Analysis (EDA)
03:02:45 – Machine Learning Types
03:14:11 – Linear Regression
06:31:15 – Logistic Regression
07:11:41 – Support Vector Machine (SVM)
07:13:23 – Decision Tree
07:15:53 – Clustering (K-Means)
08:11:10 – Data Science Project Walkthrough
09:31:45 – Data Science Interview Questions
10:37:00 – MCP Server Tutorial

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➡️ About Data Science Course:
This online Data Science course, in collaboration with iHUB, IIT Roorkee & Microsoft, will help you to elevate your Data Science career. In this course, you will master skills like Python, SQL, Statistics, Machine Learning, AI, Power BI & Generative AI, along with real-time industry-oriented projects.

➡️ Key Features:
✅ 50+ Live interactive sessions across 7 months
✅ 218 Hrs Self-paced Videos
✅ 50+ Industry relevant Projects & Quizzes
✅ Live Classes from IIT Faculty & Industry Experts
✅ Certification from iHub IIT Roorkee & Microsoft
✅ 2 Days Campus Immersion at iHub IIT Roorkee

➡️ What’s Covered in This Program?
✅ Linux and Python Fundamentals
✅ Data Wrangling with SQL
✅ Python with Data Science
✅ Linear Algebra and Advanced Statistics
✅ Machine Learning and Prediction Algorithms
✅ Supervised and Unsupervised Learning in ML
✅ Deep Learning with TensorFlow
✅ Generative AI & Prompt Engineering
✅ Deploying Machine Learning Models on Cloud
✅ Data Visualization Tool Power BI

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In this video, we will cover *Data Science Full Course 2026*, which contains topics like introduction to data science, data science life cycle, applications of data science, data science interview questions, and how to create a resume if you are an aspirant data scientist.

00:00 Data Science Full Course 2026
01:20 Data Science in 2 minutes
03:43 How to become a Data Scientist in 2021
05:20 AI vs. ML vs. DL vs. Data Science - Difference Explained
15:00 What is Data Science?
15:10 What does Data Scientist do?
31:08 What is Model Building?
56:29 Data Analyst vs. Data Engineer vs. Data Scientist in 2022
1:20:06 Introduction to statistics
1:32:11 Data Science with SAS
1:39:56 Types of Distribution in Statistics
1:58:38 Binomial Distribution
2:01:04 What is Poisson Distribution?
2:03:55 Bayes Theorem
2:06:45 What is Artificial Intelligence?
2:40:46 Introduction to Machine Learning
3:28:51 What is Machine Learning?
3:31:08 Machine Learning Algorithm
5:08:18 Classification in Machine Learning
6:42:12 Types of Machine Learning
7:44:32 K-Means clustering algorithm
8:59:20 What is Deep Learning?
9:08:10 What is a neural network?
9:40:02 Types of Python Libraries for Data Science
10:42:11 Data Science Engineer Resume
10:48:05 Data Science Interview Questions

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⏩ Check out the Data Science tutorial videos: https://www.youtube.com/watch?v=X3paOmcrTjQ&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6

#DataScienceFullCourse2023 #DataScience #IntroductionToDataScience #WhatIsDataScience #DataScienceCareers #DataScience #LearnDataScience #DataScience #DataScienceTutorial #DataScienceCourse #Simplilearn

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➡️ About Data Science Course in collaboration with IBM

This Data Science course in collaboration with IBM propels your career to become a data scientist. Gain expertise in in-demand skills like Python, SQL, Excel, Machine Learning, Tableau, generative AI, and more. Dive deep into data interpretation nuances, master Machine Learning, and enhance programming skills to elevate your Data Science career.

Key Features
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Masterclasses from IBM experts
✅ Dedicated live sessions by faculty of industry experts
✅ Industry-recognized Data Scientist Master’s certificate from Simplilearn
✅ Industry-recognized IBM certifications for IBM courses
✅ Ask-Me-Anything (AMA) sessions with IBM leadership
✅ Capstone from 3 domains and 25+ projects
✅ Exclusive hackathons conducted by IBM
✅ Lifetime access to self-paced learning content
✅ Program crafted to initiate your journey as a Data Scientist
✅ Integrated labs for hands-on learning experience

Skills Covered
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Explainable AI
✅ Conversational AI
✅ Large Language Models
✅ Model Building and Finetuning
✅ Ensemble Learning
✅ Data Visualization
✅ Database Management

👉 Learn More At: https://www.simplilearn.com/iitk-professional-certificate-course-data-analytics?utm_campaign=DataScienceFullCourse2023-6USOEP1d9HA&utm_medium=Description&utm_source=youtube

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🔥 Data Science Course (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎"): https://www.edureka.co/masters....-program/data-scient
This Edureka Data Science Full Course video will help you understand and learn Data Science Algorithms in detail. This Data Science Tutorial is ideal for both beginners as well as professionals who want to master Data Science Algorithms. Below are the topics covered in this Data Science for Beginners course:
00:00 Data Science Full Course Agenda
2:44 Introduction to Data Science
9:55 Data Analysis at Walmart
13:20 What is Data Science?
14:39 Who is a Data Scientist?
16:50 Data Science Skill Set
21:51 Data Science Job Roles
26:58 Data Life Cycle
30:25 Statistics & Probability
34:31 Categories of Data
34:50 Qualitative Data
36:09 Quantitative Data
39:11 What is Statistics?
41:32 Basic Terminologies in Statistics
42:50 Sampling Techniques
45:31 Random Sampling
46:20 Systematic Sampling
46:50 Stratified Sampling
47:54 Types of Statistics
50:38 Descriptive Statistics
55:52 Measures of Spread
55:56 Range
56:44 Inter Quartile Range
58:58 Variance
59:36 Standard Deviation
1:14:25 Confusion Matrix
1:19:16 Probability
1:24:14 What is Probability?
1:27:13 Types of Events
1:27:58 Probability Distribution
1:28:15 Probability Density Function
1:30:02 Normal Distribution
1:30:51 Standard Deviation & Curve
1:31:19 Central Limit Theorem
1:33:12 Types of Probability
1:33:34 Marginal Probability
1:34:06 Joint Probability
1:34:58 Conditional Probability
1:35:56 Use-Case
1:39:46 Bayes Theorem
1:45:44 Inferential Statistics
1:56:40 Hypothesis Testing
2:00:34 Basics of Machine Learning
2:01:41 Need for Machine Learning
2:07:03 What is Machine Learning?
2:09:21 Machine Learning Definitions
2:11:48 Machine Learning Process
2:18:31 Supervised Learning Algorithm
2:19:54 What is Regression?
2:21:23 Linear vs Logistic Regression
2:33:51 Linear Regression
2:25:27 Where is Linear Regression used?
2:27:11 Understanding Linear Regression
2:37:00 What is R-Square?
2:46:35 Logistic Regression
2:51:22 Logistic Regression Curve
2:53:02 Logistic Regression Equation
2:56:21 Logistic Regression Use-Cases
2:58:23 Demo
3:00:57 Implement Logistic Regression
3:02:33 Import Libraries
3:05:28 Analyzing Data
3:11:52 Data Wrangling
3:23:54 Train & Test Data
3:20:44 Implement Logistic Regression
3:31:04 SUV Data Analysis
3:38:44 Decision Trees
3:39:50 What is Classification?
3:42:27 Types of Classification
3:42:27 Decision Tree
3:43:51 Random Forest
3:45:06 Naive Bayes
3:47:12 KNN
3:49:02 What is Decision Tree?
3:55:15 Decision Tree Terminologies
3:56:51 CART Algorithm
3:58:50 Entropy
4:00:15 What is Entropy?
4:23:52 Random Forest
4:27:29 Types of Classifier
4:31:17 Why Random Forest?
4:39:14 What is Random Forest?
4:51:26 How Random Forest Works?
4:51:36 Random Forest Algorithm
5:04:23 K Nearest Neighbour
5:05:33 What is KNN Algorithm?
5:08:50 KNN Algorithm Working
5:24:30 What is Naive Bayes?
5:25:13 Bayes Theorem
5:27:48 Bayes Theorem Proof
5:29:43 Naive Bayes Working
5:39:06 Types of Naive Bayes
5:53:37 Support Vector Machine
5:57:40 What is SVM?
5:59:46 How does SVM work?
6:03:00 Introduction to Non-Linear SVM
6:04:48 SVM Example
6:06:12 Unsupervised Learning Algorithms - KMeans
6:06:18 What is Unsupervised Learning?
6:06:45 Unsupervised Learning: Process Flow
6:07:17 What is Clustering?
6:09:15 Types of Clustering
6:10:15 K-Means Clustering
6:10:40 K-Means Algorithm Working
6:16:17 K-Means Algorithm
6:19:16 Fuzzy C-Means Clustering
6:21:22 Hierarchical Clustering
6:22:53 Association Clustering
6:24:57 Association Rule Mining
6:30:35 Apriori Algorithm
6:37:45 Apriori Demo
6:40:49 What is Reinforcement Learning?
6:42:48 Reinforcement Learning Process
6:51:10 Markov Decision Process
6:54:53 Understanding Q - Learning
7:13:12 Q-Learning Demo
7:25:34 The Bellman Equation
7:48:39 What is Deep Learning?
7:52:53 Why we need Artificial Neuron?
7:54:33 Perceptron Learning Algorithm
7:57:57 Activation Function
8:03:14 Single Layer Perceptron
8:04:04 What is Tensorflow?
8:07:25 Demo
8:21:03 What is a Computational Graph?
8:49:18 Limitations of Single Layer Perceptron
8:50:08 Multi-Layer Perceptron
8:51:24 What is Backpropagation?
8:52:26 Backpropagation Learning Algorithm
8:59:31 Multi-layer Perceptron Demo
9:01:23 Data Science Interview Questions

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Edureka Data Science Training & Certifications

🔵 Data Science Training using Python: http://bit.ly/2P2Qbl8
🔵 Python Programming Training: http://bit.ly/2OYsVoE
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For more information, please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: +18885487823 (toll free).

This free Data Science Full Course 2026 is a complete learning path that takes you from basic concepts of Data Science to advanced data science skills in a simple and structured way. It starts by explaining what data science is, key roles, the data science life cycle, and the data science roadmap for 2026. You’ll learn how mathematics, statistics, and probability are used in real business and analytical problems. The course covers hands-on tools like Excel, Python, NumPy, and Pandas for data analysis. It also introduces machine learning, deep learning, and NLP concepts in an easy-to-understand manner. The course ends with real-world projects and interview questions to help you prepare for data science roles confidently.

Following are the topics covered in this 24 Hour Data Science Full Course 2025 By Simplilearn:

00:00:00 - Introduction to Data Science
00:05:58 - What Is Data Science?
00:08:07 - Data Scientist Vs Data Analyst In 2026
00:19:22 - Data Science Life Cycle
00:36:27 - Use Cases Of Mathematics In Data Science
00:49:57 - Statistical Analysis And Business Applications
01:13:27 - Data Science Roadmap For 2026
01:41:58 - Excel for Data Analytics 2026
00:02:51 - Data science pipeline and deployment demo
00:13:52 - NumPy fundamentals and array basics
00:46:07 - NumPy operations and special arrays
01:16:16 - Random numbers, arange/reshape, broadcasting
01:41:50 - Linear algebra and NumPy utilities
02:05:39 - Pandas: Series and DataFrame basics
02:34:10 - Reading data and practical I/O
03:01:12 - DataFrame EDA and exploration
03:25:26 - Indexing, feature engineering, sorting, cleaning
04:26:15 - GroupBy, pivot tables, and filtering
05:01:13 - Concatenation and merges
05:29:28 - Matplotlib fundamentals and chart choices
06:19:47 - Seaborn and Plotly visualizations
08:21:40 - Statistics foundations: variables and central tendency
09:15:06 - Dispersion, scaling, distributions, correlation, probability
14:47:49 - Numpy Tutorial for Data Science
17:53:24 - Pandas For Data Science
18:32:23 - Statistics For Data Science
18:55:10 - Types Of Distribution In Statistics
19:19:05 - Chi-Square Distribution
19:24:08 - Binomial Distribution In Probability
19:29:08 - Poisson Distribution In Probability And Statistics
19:32:02 - Inferential Statistics
19:37:34 - R Squared Error
19:54:51 - Mean Squared Error
19:59:39 - Probability And Binomial Distribution
20:26:26 - Probability Density Function With Example
20:50:17 - Cumulative Distribution Function Tutorial With Example
21:21:02 - Conditional Probability
21:27:25 - Bayes Theorem
21:32:09 - Supervised Vs Unsupervised vs Reinforced Learning
22:08:26 - Natural Language Processing
22:16:21 - Deep Learning With Python
22:29:43 - Top 10 Data Science Projects For 2026
23:19:29 - Data Science Interview Questions

Related Videos:
✅ 1. Python Full Course 2026 - https://youtu.be/lRfjnTYJnJ8
✅ 2. Python RAG Tutorial 2026 - https://youtu.be/WQTaM7tBlvc
✅ 3. Data Science Roadmap For 2026 - https://youtu.be/ZpINzjm_4Ks
✅ 4. FREE Data Scientist Course - https://youtu.be/_NsDrON32ww
✅ 5. Data Science Interview Questions - https://youtu.be/vtCwJKUhizg

🔥Data Scientist Masters Program (Discount Code - YTBE15) - https://www.simplilearn.com/data-science-course?utm_campaign=QISvmiwOIYI&utm_medium=Description&utm_source=Youtube
🔥Microsoft Azure - Data Analyst Course - https://www.simplilearn.com/in/data-analyst-course?utm_campaign=QISvmiwOIYI&utm_medium=Description&utm_source=Youtube
🔥Microsoft Azure - Data Analyst Course - https://www.simplilearn.com/in/data-analyst-course?utm_campaign=QISvmiwOIYI&utm_medium=Description&utm_source=Youtube

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Go from zero to a data scientist in 12 months. This step-by-step roadmap covers the essential skills you must learn to become a data scientist in 2024.

👉 Download the FREE roadmap PDF here: https://mosh.link/data-science-roadmap

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📚 Tutorials

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📖 Chapters

00:00 - Introduction
00:24 - Programming Languages
00:45 - Version Control
01:05 - Data Structures & Algorithms
01:25 - SQL
02:08 - Mathematics & Statistics
02:30 - Data Handling and Visualization
03:19 - Machine Learning
04:01 - Deep Learning
04:35 - Specialization
05:24 - Big Data

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🔥 Data Science Master Program (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎"): https://www.edureka.co/masters....-program/data-scient
This Edureka video on "Data Science Full Course" provides an end to end, detailed and comprehensive knowledge on Data Science. This Data Science video will start with basics of Statistics and Probability and then moves to Machine Learning and Finally ends the journey with Deep Learning and AI. For Data-sets and Codes discussed in this video, drop a comment. This Data Science tutorial will be covering the following topics:

1:23 Evolution of Data
2:14 What is Data Science?
3:02 Data Science Careers
3:36 Who is a Data Analyst
4:20 Who is a Data Scientist
5:14 Who is a Machine Learning Engineer
5:44 Data Scientist Salary Trends
6:37 Data Scientist Road Map
9:06 Data Analyst Skills
10:41 Data Scientist Skills
11:47 Machine Learning Engineer Skills
12:53 Data Science Peripherals
13:17 What is Data ?
15:23 Variables & Research
17:28 Population & Sampling
20:18 Measures of Center
20:29 Measures of Spread
21:28 Skewness
21:52 Confusion Matrix
22:56 Probability
25:12 What is Machine Learning?
25:45 Features of Machine Learning
26:22 How Machine Learning works?
27:11 Applications of Machine Learning
34:57 Machine Learning Market Trends
36:05 Machine Learning Life Cycle
39:01 Important Python Libraries
40:56 Types of Machine Learning
41:07 Supervised Learning
42:27 Unsupervised Learning
43:27 Reinforcement Learning
46:27 Supervised Learning Algorithms
48:01 Linear Regression
58:12 What is Logistic Regression?
1:01:22 What is Decision Tree?
1:11:10 What is Random Forest?
1:18:48 What is Naïve Bayes?
1:30:51 Unsupervised Learning Algorithms
1:31:55 What is Clustering?
1:34:02 Types of Clustering
1:35:00 What is K-Means Clustering?
1:47:31 Market Basket Analysis
1:48:35 Association Rule Mining
1:51:22 Apriori Algorithm
2:00:46 Reinforcement Learning Algorithms
2:03:22 Reward Maximization
2:06:35 Markov Decision Process
2:08:50 Q-Learning
2:18:19 Relationship Between AI and ML and DL
2:20:10 Limitations of Machine Learning
2:21:19 What is Deep Learning ?
2:22:04 Applications of Deep Learning
2:23:35 How Neuron Works?
2:24:17 Perceptron
2:25:12 Waits and Bias
2:25:36 Activation Functions
2:29:56 Perceptron Example
2:31:48 What is TensorFlow?
2:37:05 Perceptron Problems
2:38:15 Deep Neural Network
2:39:35 Training Network Weights
2:41:04 MNIST Data set
2:41:19 Creating a Neural Network
2:50:30 Data Science Course Masters Program

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Post Graduate Certification in Data Science with IIT Guwahati - https://www.edureka.co/post-gr....aduate/data-science-
(450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies)

#edureka #DataScienceEdureka #whatisdatascience #Datasciencetutorial #Datasciencecourse #datascience


- - - - - - - - - - - - - -

About the Master's Program

This program follows a set structure with 6 core courses and 8 electives spread across 26 weeks. It makes you an expert in key technologies related to Data Science. At the end of each core course, you will be working on a real-time project to gain hands on expertise. By the end of the program you will be ready for seasoned Data Science job roles.

- - - - - - - - - - - - - -

Topics Covered in the curriculum:

Topics covered but not limited to will be : Machine Learning, K-Means Clustering, Decision Trees, Data Mining, Python Libraries, Statistics, Scala, Spark Streaming, RDDs, MLlib, Spark SQL, Random Forest, Naïve Bayes, Time Series, Text Mining, Web Scraping, PySpark, Python Scripting, Neural Networks, Keras, TFlearn, SoftMax, Autoencoder, Restricted Boltzmann Machine, LOD Expressions, Tableau Desktop, Tableau Public, Data Visualization, Integration with R, Probability, Bayesian Inference, Regression Modelling etc.

- - - - - - - - - - - - - -

For more information, Please write back to us at sales@edureka.in or call us at:
IND: 9606058406 / US: 18338555775 (toll free)

Learn Data Science is this full tutorial course for absolute beginners. Data science is considered the "sexiest job of the 21st century." You'll learn the important elements of data science. You'll be introduced to the principles, practices, and tools that make data science the powerful medium for critical insight in business and research. You'll have a solid foundation for future learning and applications in your work. With data science, you can do what you want to do, and do it better. This course covers the foundations of data science, data sourcing, coding, mathematics, and statistics.

💻 Course created by Barton Poulson from datalab.cc.
🔗 Check out the datalab.cc YouTube channel: https://www.youtube.com/user/datalabcc
🔗 Watch more free data science courses at http://datalab.cc/

❤️ Try interactive Algorithms courses we love, right in your browser: https://scrimba.com/freeCodeCamp-Algorithms (Made possible by a grant from our friends at Scrimba)

⭐️ Course Contents ⭐️
⌨️ Part 1: Data Science: An Introduction: Foundations of Data Science
- Welcome (1.1)
- Demand for Data Science (2.1)
- The Data Science Venn Diagram (2.2)
- The Data Science Pathway (2.3)
- Roles in Data Science (2.4)
- Teams in Data Science (2.5)
- Big Data (3.1)
- Coding (3.2)
- Statistics (3.3)
- Business Intelligence (3.4)
- Do No Harm (4.1)
- Methods Overview (5.1)
- Sourcing Overview (5.2)
- Coding Overview (5.3)
- Math Overview (5.4)
- Statistics Overview (5.5)
- Machine Learning Overview (5.6)
- Interpretability (6.1)
- Actionable Insights (6.2)
- Presentation Graphics (6.3)
- Reproducible Research (6.4)
- Next Steps (7.1)

⌨️ Part 2: Data Sourcing: Foundations of Data Science (1:39:46)
- Welcome (1.1)
- Metrics (2.1)
- Accuracy (2.2)
- Social Context of Measurement (2.3)
- Existing Data (3.1)
- APIs (3.2)
- Scraping (3.3)
- New Data (4.1)
- Interviews (4.2)
- Surveys (4.3)
- Card Sorting (4.4)
- Lab Experiments (4.5)
- A/B Testing (4.6)
- Next Steps (5.1)

⌨️ Part 3: Coding (2:32:42)
- Welcome (1.1)
- Spreadsheets (2.1)
- Tableau Public (2.2)
- SPSS (2.3)
- JASP (2.4)
- Other Software (2.5)
- HTML (3.1)
- XML (3.2)
- JSON (3.3)
- R (4.1)
- Python (4.2)
- SQL (4.3)
- C, C++, & Java (4.4)
- Bash (4.5)
- Regex (5.1)
- Next Steps (6.1)

⌨️ Part 4: Mathematics (4:01:09)
- Welcome (1.1)
- Elementary Algebra (2.1)
- Linear Algebra (2.2)
- Systems of Linear Equations (2.3)
- Calculus (2.4)
- Calculus & Optimization (2.5)
- Big O (3.1)
- Probability (3.2)

⌨️ Part 5: Statistics (4:44:03)
- Welcome (1.1)
- Exploration Overview (2.1)
- Exploratory Graphics (2.2)
- Exploratory Statistics (2.3)
- Descriptive Statistics (2.4)
- Inferential Statistics (3.1)
- Hypothesis Testing (3.2)
- Estimation (3.3)
- Estimators (4.1)
- Measures of Fit (4.2)
- Feature Selection (4.3)
- Problems in Modeling (4.4)
- Model Validation (4.5)
- DIY (4.6)
- Next Step (5.1)

--

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𝐄𝐝𝐮𝐫𝐞𝐤𝐚'𝐬 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐌𝐚𝐬𝐭𝐞𝐫𝐬 𝐩𝐫𝐨𝐠𝐫𝐚𝐦: https://www.edureka.co/masters....-program/data-scient
🔥Data Science with Python Certification Course: https://www.edureka.co/data-sc....ience-python-certifi
🔥Integrated MS+PGP Program in Data Science & AI:https://www.edureka.co/dual-ce....rtification-programs
This Edureka Data Science Full Course video will help you understand and learn Data Science Algorithms in detail. This Data Science Tutorial is ideal for both beginners as well as professionals who want to master Data Science Algorithms.
00:00:00 Introduction
00:01:31 What is Data Science?
00:03:26 Who is a Data Scientist?
00:35:36 Top 10 Reasons to Learn Data Science
00:40:12 Data Science Basics
01:33:28 Data Life Cycle
01:37:03 Statistics and Probability
03:09:33 Hypothesis Testing Statistics
04:02:26 What is Machine Learning?
04:19:21 Linear Regression
04:45:59 Logistic Regression
05:34:29 Decision Tree Algorithm
06:19:50 Random Forest
06:47:02 KNN Algorithm
07:19:27 Naive Bayes Classifier
07:39:45 Support Vector Machine
08:05:14 K- Means Clustering Algorithm
08:25:22 Apriori Algorithm Explained
08:55:04 Reinforcement Learning
09:16:30 What is Deep Learning?
09:40:24 Introduction to Keras
10:11:51 Data Science Roadmap
10:21:05 Data Science vs Data Analytics
10:31:05 Data Science for Non Programmers
10:59:00 Data Science Interview Questions

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Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: +18885487823 (toll-free) for more information.

In this video, you’ll get a complete introduction to data analytics, starting from the basics and gradually moving toward practical, job-ready skills. We begin with Python fundamentals and then cover powerful libraries like NumPy and Pandas to help you understand how real-world data is handled and processed efficiently.

As the video progresses, you’ll learn how to visualize data using Matplotlib and Seaborn, followed by essential EDA techniques to uncover patterns and insights. We also explore Excel for analysis and SQL for working with databases, giving you a strong foundation in data analytics tools used across industries.

Towards the end, the focus shifts to Power BI for interactive dashboards and real-world project ideas that help you apply what you’ve learned. Whether you’re a beginner or planning to upskill, this video offers a structured learning path in data analytics to help you build confidence and practical experience.

​​Access the study material from the given link- https://forms.gle/6R1BFmEDfJTXrekf6

📖 Below are the concepts covered in the video on “Data Analytics Full Course”:
00:00:00 – Introduction to Data Analytics Course
00:01:25 – Python Basics
02:16:00– Numpy Arrays
02:28:03– Pandas Operations
03:34:08 – Matplotlib Visualisations
03:43:04 – Seaborn Styling
03:54:33 – EDA Techniques
03:54:33 – Excel For Data Analytics
05:11:37 – SQL
08:08:55 – Power BI
09:58:36 – Data Analytics Project Ideas

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🔥Enroll for Data Analytics: https://intellipaat.com/data-a....nalytics-master-trai

➡️ About the Course
The Data Analytics Master Training Course by Intellipaat is an online program designed to help learners build strong data analytics skills from basics to advanced levels. It covers key tools like Python, SQL, Excel, Power BI, and PySpark, along with essential concepts such as data cleaning, EDA, statistics, and data visualization. The course includes real-world projects and case studies, making it suitable for beginners as well as professionals looking to upskill or transition into analytics roles.

✅ Key Features
👉🏼50+ live sessions over ~7 months with industry experts and IIT faculty.
👉🏼218+ hours of self-paced video tutorials.
👉🏼200+ hours of hands-on projects and exercises.
👉🏼One-on-one mentorship and industry guidance.
👉🏼LinkedIn profile review and resume assistance.
👉🏼24×7 support and doubt resolution.
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👉🏼Placement assistance and access to a large hiring network.
👉🏼Certification including Data Analytics credentials and IIT-linked recognition.

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📚For more information, please write back to us at sales@intellipaat.com or call us at IND: +91-7022374614 / US : 1-800-216-8930

Top pick Data Analyst course: Datacamp Data Analyst with Python Career Track (https://datacamp.pxf.io/BnEVgB)

Get access to my top 10 data analyst certificates list: https://www.skool.com/9-5-to-dream-life

- How to actually learn Data Analysis?
- Which are the best Data Analyst certifications?
- How to become a Data Analyst?

This video will answer those questions.

💻 Course links:
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3. Datacamp Data Analyst Career Track: https://datacamp.pxf.io/BnEVgB
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Microsoft Power BI Data Analyst (Exam preparation + 50% discount):
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