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Special Thanks to Abhishek Goyal and Anindya Prithvi for providing resources

Jump to specific semester

IP DC LA HCI COM
DSA P&S BE CO
AP OS DM DS M3
DBMS ITS ADA M4 PIS TOC SML PB GT
NLP ML CN RL CG EVS
ATP

IIIT Sem 1 Resources

Best Prep Guide

IP

DC

Linear Algebra

HCI

Comms


IIIT Sem 2 Resources

DSA

Probability

Basic Electronics

Computer Organization

SSH Courses


IIIT Sem 3 Resources

AP

OS

Discrete Maths

Discrete Structures

Mathematics III (Multivariate Calculus)

Signals and Systems

KCES


IIIT Sem 4 Resources

DBMS

ITS

ADA

M4

  • Do The Book
  • Do The Book
  • Do The Book
  • Google Topics you find difficult probably Gajendra Purohit Sir, BPRP or someone else has a video on it

PIS

  • IDK NO THEORY

TOC

Statistical ML (CSE342)

  • Lecture Slides and/or https://scikit-learn.org/stable/user_guide.html
    • The above is not an API only page, you will find a lot of content for reading.
  • Do not do [Christopher M. Bishop - Pattern Recognition and Machine Learning-Springer (2006)]
    • contains wrong information or inconsistent with class.

Practical Bioinformatics (BIO221)

Graph Theory (very easy course)

  • Introduction to Graph Theory by Douglas B. West
    • Note, the course is not on algorithms

IIIT Sem 5 Resources

NLP

ML

CN

RL (Reinforcement Learning)

Computer Graphics

  • Peter Shirley, Fundamentals of Computer Graphics (course book, often reffered)
  • SIGGRAPH Intro to opengl video
  • docs.gl

EVS


IIIT Sem 6 Resources

ATP


Course Books : here