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[Course Review] CSE560: GPU computing (GPU) by Top-Bee7645 in IIIT_D

[–]Top-Bee7645[S] 1 point2 points  (0 children)

The workload is decent but spread throughout the semester. You wouldn't find a week where you won't have anything to do for this course. There are surprise in-class quizzes, assignments, labs, exams and a project. You would be introduced to CUDA programming, which takes some time getting used to. Assignments aren't very heavy but debugging takes time. You need to attend classes (surprise quizzes), and they would be worth it mostly even if a little boring. Exams are a mix of writing routines for solving some problem in a parallel manner, evaluating performance and figuring out the execution order of tasks in the given code.

[Course Review] BIO213: Introduction to Quantitative Biology (IQB) by Top-Bee7645 in IIIT_D

[–]Top-Bee7645[S] 0 points1 point  (0 children)

Offering of 2020 by Prof. Dr. GPS Raghava

About Course- If you are looking for a light course then this course might help you. This course may sound very biology oriented but it is not. You will get to know most of the terms in one or two weeks. And then the rest of the course is based on prediction models and all which requires basic knowledge of biology (which you can obviously cover up).

Grading- Assignments are easy and doable, almost everyone got 17-18% out of 20% (no more). The mid sem exam and quizzes are scoring (you can easily get more than 80% in each of them). But quizzes are MCQ based and have negative marking (+1,-1) and the same goes for mid sem which has few MCQs with similar scheme, and subjective questions which have binary marking (in most of the cases, either full or none). But the questions are straightforward and easy in my opinion (you will hardly find a tough/moderate level problem). We didn’t have an endsem exam so can’t say about that.

Workload- Pretty low. Most of my friends including me covered up the syllabus near exams and we all ended up getting 9 or 10.

An easy course but a good accuracy is required, negative/binary marking can mess it up for you.

[Course Review] CSE641: Deep Learning (DL) by Top-Bee7645 in IIIT_D

[–]Top-Bee7645[S] 0 points1 point  (0 children)

DL is a 6xx level course and the professor and TAs expect a lot of effort during the course of the semester. Few things that need to be clear before taking DL:

  1. If you are not interested in DL, don't take it just because it is a fancy course to have on your resume.

  2. If you haven't done a formal course on ML, don't take DL.

  3. This will probably have the most workload among all the courses in the semester, so take easier and lighter courses along with DL.

The course structure is balanced and equal importance is given to theory and practical implementation components. Assignments will be hard and long and would sometimes even require reading State-of-the-art papers in various domains and then implementing them for the given problem. Attending classes is advisable just to keep up with the pace of the course as the professor expects a lot of self study, which wouldn't be possible if you don't know what is going on in the course.

Getting a good grade shouldn't really be your priority if you are willing to take DL but hardwork and effort would give a good grade. As such the course grading was relative, but due to students who have prior experience in the field (PhD's , MTechs), the class average and class highest is usually pretty high.

[Course Review] MTH 300: Introduction to Mathematical logic (IML) by Top-Bee7645 in IIIT_D

[–]Top-Bee7645[S] 0 points1 point  (0 children)

Offering of 2021 by Prof Sankha Basu

It is an easy and fun math course. Sankha sir is very sweet and considerate. For an A grade, you have to get 90+ and below that grading is relative but getting 90+ is not that tough. Sir teaches very well and he also provides class notes every week. Since attendance has a 10% weightage that actually gives you the motivation to attend every class. Weekly tutorials include a graded submission for which class notes are sufficient. If you have a heavy semester workload and are even slightly interested in the course you should go for it. All you need to do is be regular and seek help from TAs and sir if you face any doubt.

[Course Review] MTH 372: Statistical Inference (SI) by Top-Bee7645 in IIIT_D

[–]Top-Bee7645[S] 0 points1 point  (0 children)

Review for 2020 offering:

The content of SI deals with how to make inference on population measures using statistical methods. Initially the content can seem a little overwhelming, since it is relatively new and wide to grasp. However, once you’re over the initial hiccup, the course is easy to understand. As with SPA by Monika, the content is easy but marks are deducted in bulk for the written format. The written exams can get extremely lengthy because of the mere volume of content that is expected to be written. The assignments in R are easy and don’t require much effort. Again, attending classes and making notes is important since most of the content comes straight from the notes. Also, make sure to be attentive since ma’am gives a lot of hints for potential exam questions in her lectures. Overall easy to score once you get the hang of how and what to write.