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GATE(DA) Preparation Material

This article provides a curated list of study resources for the GATE Data Science & Artificial Intelligence (DA) exam. It recommends foundational mathematics from NCERT Class 11 and 12 textbooks, along with advanced video playlists from MIT, IITs, and creators like 3Blue1Brown for topics such as linear algebra, probability, and calculus. The guide also includes materials for computer science subjects like algorithms, databases, and machine learning, featuring courses from professors like Gilbert Strang and Mitesh Khapra.

read3 min views21 publishedJun 22, 2024
- Mathematics (Class 11 & 12) - NCERT Relevant Chapters
- Class 11 - Ch 1. Sets
  • Class 11 - Ch 2. Relations and Functions
  • Class 12 - Ch 1. Relations and Functions
  • Class 11 - Ch 6. Permutations and Combinations
- Class 11 - Ch 7. Binomial Theorem
- Class 11 - Ch 8. Sequences and Series
- Class 11 - Ch 13. Statistics
- Class 11 - Ch 14. Probability
- Class 12 - Ch 13. Probability
- Intro to Probability (RES.6-012), Spring 2018 - Prof. John N. Tsitsiklis - MIT - YouTube Playlist - 30 Hours
  • ProbabilityCourse.com - Online Textbook on Probability, Statistics & Random Processes
  • 50 Challenging Problems in Probability - Frederick Mosteller - Dover Publications' Book
- Essence of Linear Algebra - 3Blue1Brown (Grant Sanderson) - YouTube Playlist - 3 Hours
- Mathematics (Class 11 & 12) - NCERT Relevant Chapters
- Class 11 - Ch 9. Straight Lines
- Class 12 - Ch 3. Matrices
- Class 12 - Ch 4. Determinants
- Class 12 - Ch 10. Vector Algebra
- Linear Algebra (18.06SC), Fall 2011 - Prof. Gilbert Strang - MIT - YouTube Playlist - 36 Hours
- Essence of calculus - 3Blue1Brown (Grant Sanderson) - YouTube Playlist - 4 Hours
- Mathematics (Class 11 & 12) - NCERT Relevant Chapters
  • Class 11 - Ch 12. Limits and Derivatives
  • Class 12 - Ch 5. Continuity and Differentiability
  • Class 12 - Ch 6. Application of Derivatives
  • Class 12 - Ch 7. Integrals
  • Class 12 - Ch 8. Application of Integrals
  • Class 12 - Ch 9. Differential Equations
- Numerical Optimization - Prof. Shirish Shevade - IISc - YouTube Playlist - 38 Hours
- Introduction to Algorithms (6.006), Spring 2020 - MIT - YouTube Playlist - 36 Hours
- Python for Beginners (Full Course) - Navin Reddy (Telusko) - YouTube Playlist - 16 Hours
  • Competitive Programmer's Handbook - Antti Laaksonen - Online Textbook
  • Database Management System - Prof D. Janakiram & Prof. S. Srinath - IIT Madras - YouTube Playlist - 41 Hours
  • Database Management & Warehousing - Piyush Wairale (M.Tech Alumni & Teaching Fellow @ IIT Madras) - YouTube Playlist - 7 Hours
- Deep Learning Prerequisites: Numpy Stack V2 - Udemy
- Neural Networks - 3Blue1Brown - YouTube Playlist - 2 Hours
- Introduction to Deep Learning (6.S191) - Alexander Amini - MIT - YouTube Playlist (Watch Any Year) ~ 8 Hours (per year)
  • Hands-On ML with Scikit-Learn, Keras, and TensorFlow, 3rd Edition - Aurelien Geron - Oreilly's Book
- Introduction to Machine Learning (CS771) - Prof. Piyush Rai - IIT Kanpur - YouTube Playlist - 28 Hours
- Pattern Recognition - Prof. P. S. Sastry - IISc - YouTube Playlist - 40 Hours
- Deep Learning Part 1, Part 2 - Prof. Mitesh Khapra - IIT Madras - YouTube Playlist - 38 Hours
- **Artificial Intelligence (6.034), Fall 2010
- An Introduction to AI - Prof. Mausam - IIT Delhi - Playlist - 33 Hours
- AI Search Methods For Problem Solving - Prof. Deepak Khemani - IIT Madras - Playlist - 41 Hours

Note 1: On NCERT Mathematics books of Class 11 and 12, I would recommend if you can solve them end-to-end during your preparation (specially the miscellaneous problem at end of each chapter) Note 2: Below are two non-technical videos. But might help you get started

  • The Slow Poison of Endless Fantasy - After Skool - YouTube
  • What "Follow Your Dreams" Misses - 3Blue1Brown (Grant Sanderson) - YouTube
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