The Complete Machine Learning & Data Science Program is a comprehensive live course designed to take you from beginner to expert in machine learning and data science. Explore a 360-degree learning experience designed for geeks who wish to get hands-on Data Science and ML. Mentored by industry experts; learn to apply DS methods and techniques, and acquire analytical skills. Join us to gain practical knowledge and become proficient in Data Science.
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The Complete Machine Learning & Data Science Program by GeeksforGeeks is an all-encompassing course designed to take you from a beginner to an advanced level in the world of data science and machine learning.
This 6-month live Data Science course is perfect for tech enthusiasts, students, and professionals alike who are eager to gain hands-on experience in the data science field. The complete Data Science course covers a wide array of topics, starting with Python programming basics and essential data science libraries like Numpy and Pandas.
Learn data analytics, machine learning algorithms, and AI concepts, ensuring you build a strong foundation. You will also explore specialized areas like deep learning, image processing, and natural language processing (NLP). With 20+ programming tools and libraries, 40+ industry-relevant projects, and live sessions with industry mentors, this Complete Machine Learning & Data Science Program provides a robust and practical learning experience.
Project-Based Learning
24 X 7 Doubt Support
Expert Mentors
Hands-on, practical exercises designed to enhance your learning experience and reinforce the concepts covered in the course. These projects serve as crucial components in the learning journey, as they allow you to apply the knowledge and skills gained in real-world scenarios. Eg: Wikipedia Scraper, PubG Predictive Analysis, Spell Checker & many more.
Hands-on, practical exercises designed to enhance your learning experience and reinforce the concepts covered in the course. These projects serve as crucial componen
A dedicated service provided with this course for free to help you overcome any doubt, at any time, and anywhere. So unlea
With a passion for teaching, our mentor(s) sessions will provide tailored guidance to all the aspiring coders. Launch a successful tech career with
Introducing Python - Python Basics, Operators, Loops, Functions, Strings, List, Tuples, Dictionary, Set, Object-oriented concepts(OOPs) and much more.
Data Toolkit - Getting started with Files, Inventory Management System with Files, Inventory Management System with JSON, Mastering Numpy Arrays, Getting Started with OS , Jupyter Notebook Setup, OS with Python, etc.
Libraries - Numpy, Pandas, Matplotlib, Streamlit, etc.
Maths for Data Analysis: Basic Probability for Data Science, Statistics, Probability Distribution, Inferential Statistics, and much more
Maths for ML & AI: System of Linear Equation, Matrix, Vectors, and Calculus, etc
Data Analysis with Python: Getting started with Pandas, Data Preprocessing with Google Play store, Introduction to EDA, Data Cleaning, Data Visualization, Data Analysis
Projects: Sugarcane Production, Black Friday Sales Data Analysis, Data Visualization on Heart Disease Dataset, GDP Analysis
Excel: Exploring Data, Preparing Data, Analysing Data, Important Interview Questions
Projects: Sales Data Analysis Using Covered Functions and Pivot Tables
Power BI - Introduction to Power BI, Understanding Parameters, Basic Plots, Fundamentals of Power BI, Designing the Plots, etc
Projects: Superstore Sales Analysis Dashboard, Covid-19 World Dashboard
Web Scraping - Learn how to Scrape, Selenium, Image Dataset Creation, and much more
Projects: Wikipedia Scraper, Youtube Scrapper, Stock Images Infinite Scroll
SQL - Databases Fundamentals, SQL Fundamentals, Data Manipulation(DML), Querying, Intermediate SQL Queries, Joining and combining Data, Set Theory Clauses, Subqueries, Window Functions, Data Preprocessing and analysis
Introduction to AI, How Data Science Comes into Play,
Linear Regression, Multiple Linear Regression & Polynomial Linear Regression,
Support Vector Machines, Decision Trees, Random Forests,
Classification Algorithms, Clustering Algorithms, Feature Engineering, and much more