- 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
@Harshit07979 there is a priority when you are learning things. Understanding concepts and reasoning should be first, solving GATE style questions should be second. Post that you can within 1-2 days create brief notes, by solving questions you will also realise what you should put more in notes, and what you can skip. I highly recommend hands-on in Python for both DSA and ML, but considering the limited time for upcoming GATE 2025, that can be avoided. But if you are in 3rd year or early, doing the same for any concept will push it into your memory 10x stronger if you code it down for yoursel