Course Name: IQIC
By prof: Indraneel Chakraborty

Author: Shivansh S

Advise: Honestly, just go through it and listen, its mostly fun but nothing too serious that you have to pay attention to. Greenberg's Universals are the only important thing, and other than that, learning from Wiki and Google is more effecient than learning from book

Resource Name: Remzi Spring'18 and OSTEP

Contributor (your) Name: Shashwat Goel

Resource Links: http://pages.cs.wisc.edu/~remzi/Classes/537/Spring2018/

Have you completed studying this resource?: Lectures yes, book and homework no.

Your review of this resource: The lectures are great for an intuitive understanding

Why do you think this resource will be useful for others?: OSN course at IIIT uses a boring graduate textbook with a lot of detail. Since the teaching is poor, achieving clarity of concepts or finding the coursework interesting is almost impossible without learning elsewhere. Hence, using the intuitive lectures here and the conceptual easy-to-read book (OSTEP) can be useful to most.

Real Analysis

A Kishore Kumar

https://math.mit.edu/~jorloff/18.04/notes/, https://www.coursera.org/learn/complex-analysis, https://www.youtube.com/watch?v=5PcpBw5Hbwo, https://www.youtube.com/watch?v=YcornNekVao

Partially

Excellent explanations in the Coursera course along with examples and in-video questions. Do till week 4. Great explanations in the OCW notes. Linked video of 3b1b and the one following that are pretty much the best visualizations for understanding complex numbers that you'll find on the internet. A quick rundown on contour integration formulae.

Clear and concise explanations. Great visuals and some also provide mini questions to keep you engaged and test understanding quickly instead of spending time working out stuff later on when you don't have any motivation to.

Course Name: Automata Theory
by prof: Kannan Srinathan

Resource Names:

1. Probability Course by Pishro-Nik
2. Introduction to Probability, Tsitsiklis

Contributor (your) Name: Alapan Chaudhuri

Resource Links:

1. https://www.probabilitycourse.com/,
2. https://vfu.bg/en/e-Learning/Math--Bertsekas_Tsitsiklis_Introduction_to_probability.pdf

Have you completed studying this resource?: Around 80%, haven't solved all problems.

Your review of this resource: Probability Course covers almost all necessary topics precisely. If you need help in understanding the proof (etc.) you can always do a quick google search. Tsitsiklis is also quite concise with respect to several textbooks on the subject. It has quite a good set of example problems and theorem compilations (per chapter). It has proper proofs too and overall both of the resources serve as excellent references.

Why do you think this resource will be useful for others?: Rather than clumsy old books/lecture series, you can follow these since they are concise yet complete as well as easy-to-read with lots of examples.

Resource Name: OS course by Mythili Vutukuru (Prof at IIT Bombay) (lectures and notes) along with content related to XV6

Contributor (your) Name: Anmol Agarwal

Resource Links:
Link 1 to lecture notes (2016 version) : https://www.cse.iitb.ac.in/~mythili/teaching/cs347_autumn2016/index.html
Link 2 to XV-6 content (2020 version) : https://www.cse.iitb.ac.in/~mythili/os/
Link 3 to lectures: https://youtube.com/playlist?list=PLTtjs-HViBW7HPvOPDNarA-e1WAU23tKG

Have you completed studying this resource?: The course seems to be divided into 7 parts: A,B,C,D,X,N,Z. Parts A,B,C,D have accompanying lectures. Some parts reference the OSTEP Three Easy Pieces as lecture notes while the other parts have notes compiled by the instructor herself.
I have viewed lectures and read notes of parts A,B,C,D and X. Haven't done the assignments here.

Your review of this resource: The lectures have great clarity content wise and the notes (the ones which have been compiled by the instructor herself) are extremely concise,well-written(Eg:https://www.cse.iitb.ac.in/~mythili/teaching/cs347_autumn2016/notes/02-processes-threads.pdf) and the sequence in which topics are covered is perfect.

Why do you think this resource will be useful for others?:
The lectures by the IIIT instructor (in Monsoon 2020) were boring and did not add anything to the content already covered by the course textbook(Silberschatz). Prof Vutukuru uses the OSTEP book as the main reference textbook (which helps if you are already planning to use the OSTEP Three Easy Pieces book) and the lecture videos are short (~20 min) but still more insightful and informative than the entire course at IIIT. Even if you don’t have enough time to view the lectures, the written notes (in link 1) are likely to confirm several of your own thoughts, conclusions, insights etc which you derive from the course.

Course Name: Intro to Brain and Cognition
By prof: Bapi Raju, Kavitha Vemuri

Resource Name: Intro to Computer Systems (CMU course website for IIIT equivalent Computer Systems Organization course and lectures by Bryant and O'hallaron)

Contributor (your) Name: Anmol Agarwal

Resource Links:
Link to slides : http://www.cs.cmu.edu/afs/cs/academic/class/15213-f15/www/schedule.html
Link to lectures: https://scs.hosted.panopto.com/Panopto/Pages/Sessions/List.aspx#folderID=%22b96d90ae-9871-4fae-91e2-b1627b43e25e%22

Have you completed studying this resource?: I watched lectures 1 to 8 and lecture 12 and referenced the slides as and when needed.

Your review of this resource: The lecturers are extremely knowledgeable (they are the authors of an extremely well-written book after all) and the discussions between the students and the lecturer are often very insightful.

Why do you think this resource will be useful for others?:
The lectures by the IIIT instructor (in Spring 2020) were often lacking in clarity (even though the instructor tried to put effort) and the slides’ content was exactly the same as the content in the book ‘Computer Systems: A Programmer's Perspective’ by Bryant and O'hallaron and hence, classes are likely to be a waste of time. The book is extremely well-written and the lectures by Bryant and O’hallaron supplement the book pretty well. The discussions between the students and lecturer accompanied by the great content delivery in the lectures makes it well worth watching.

Course Name: Introduction to NLP
prof: Manish Srivastava

Course Name: MDL
by prof: Praveen Paruchuri

Resource Name: MIT 18.06 Linear Algebra - MIT OCW

Contributor (your) Name: Animesh Das

Resource Links: https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/

Have you completed studying this resource?: Yes. Needed it for MA4.404 (Functional Analysis)

Your review of this resource: Easy to follow. It helped me brush up on vector spaces.

Why do you think this resource will be useful for others?: Most of the basic IIIT courses are easier with a little help from MIT. Atleast before 2018, Gilbert Strang's "Linear Algebra and Its Applications" was the standard textbook for our Linear Algebra equivalent, Maths-II.

Author: Shivansh S

Advise: Do not miss the classes, Manish teaches it slowly but gives beautiful intuition of everything that happens. Coding up the ideas will be tough but go through it, its worth it.

Course Name: Statistical Methods in AI (CS7.403)

Course Name: Algorithms Analysis & Design

Resource Name: Intro-to-NLP1

Contributor (your) Name: Shivansh S

Resource Links: https://github.com/AurumnPegasus/Intro-to-NLP1

Have you completed studying this resource?: I mean I compiled it so yea 😛

Your review of this resource: Gives an in depth epxlanation of execution of the code which are required in the course

Why do you think this resource will be useful for others?: From a cld perspective, I felt that the jump NLP1 made from cl2 to nlp1 was huge, and majority of the time I had to spend was on coding and understanding of how to code stuff up. Hence the repo I have linked have code with algorithms explained with execution.

1. Statistical: Explains properly the alogirthms used for Kneyser Ney and Witten Bell smoothing, and their execution
2. Neural: Explains in depth of all the decisions which I took to create a basic Language Model. This also explains dimensions properly, which I felt was the toughest part to understand with respect to NNs.

Resource Name: PyTorch: NLP from scratch

Contributor (your) Name: Shivansh S

Resource Links: https://pytorch.org/tutorials/intermediate/char_rnn_classification_tutorial.html

Have you completed studying this resource?: Yes

Your review of this resource: Kinda hand wavy, but a good introduction on how to use pytorch

Why do you think this resource will be useful for others?: It helps understanding and making the first Neural Network using LSTMs. Helpful if its the first time, but it often becomes hand wavy at some points and you might need to google around to properly understand whats happening. I would recommend to go through it, and make it (atleast the first 2 parts) but do not consider it as a bible when trying to code

Resource Name: Introduction To Computer Networking

Contributor (your) Name: Kunwar Shaanjeet Singh Grover

Resource Links:

1. Videos: https://www.youtube.com/playlist?list=PLEAYkSg4uSQ2dr0XO_Nwa5OcdEcaaELSG
2. Assignments: https://github.com/PrincetonUniversity/COS461-Public

Have you completed studying this resource?: Completed 6/8 sections

Your review of this resource: Video letures are lengthy but really good. The demos using wireshark and shell utilities in between lectures are really helpful in understanding the topics practically. Watching this course alone can be boring. Pick atleast one person along with you to watch as the topics can get hard to grasp at times and can become boring.

Why do you think this resource will be useful for others?: IIIT Prof tries to cover a very heavy book in less than a month time and usually is very theoretical with no history, reasons or demos (particularly this). This course is much better than trying to understand inclass lectures. Another thing worth mentioning is that i tried finding various resources to study networking from and found this to be the best one according to me.

Course Name: Intro to Coding Theory
Professor: Lalitha Vadlamani

Resource Name: 3b1b

Contributor (your) Name: Shivansh S

Resource Links: https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi

Have you completed studying this resource?: Yes

Your review of this resource: Absolute Beauty

Why do you think this resource will be useful for others?: Gives a very coherent and basic explanation of how neural networks work, and gives the perfect amount of math intuition require to understand what exactly is happening. My advice is to go through this before Manish starts talking about LSTMs

Resource Name: xv6 Resources

Contributor (your) Name: Kunwar Shaanjeet Singh Grover

Resource Links:

1. https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-828-operating-system-engineering-fall-2012/lecture-notes-and-readings/MIT6_828F12_xv6-book-rev7.pdf
2. https://github.com/YehudaShapira/xv6-explained

Have you completed studying this resource?: Read relevant parts for xv6 assignments

Your review of this resource: (1) is the official book with explanations that comes with xv6. (2) Are some great explanations of how and each and every part of it works. Great explanations which make you understand how things in a kernal actually work. For example a thing you can try to find yourself is "how does sleep syscall work in a kernal?"

Why do you think this resource will be useful for others?: From what I saw in my batch, most people either copied the xv6 assignments or did not actually understand what and how they were doing it. These resources help you understand and will enhance what you will learn from that assignment or from xv6 in general.

Author: Shashwat Goel

Advice: Don't miss any class, you won't get this quality of teaching at IIIT again :)

Course Name: LTU (Language Typology and Universals)

C Programming

Real Analysis

Course Name: Digital Image Processing (CS7.404)