- 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
Hi @rrdhanush, I'd recommend if you can read the concepts and solve the miscellaneous exercises that should suffice. But if you struggle with this, anything advanced would not make much sense