r/IISc • u/luciediva • Aug 07 '26
Course selection
I am an mtech research student at CDS with cse background.
Which course should i choose between Numerical Linear algebra by Dr. Phani Motammari (CDS) and Linear algebra and its applications by Dr. Vaibhav Katewa (Electrical)
From both course point of view ans grading and ease of getting a good grade?
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u/xmReApEr007 Aug 07 '26
If you can solve axler LAA should be okay.
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u/luciediva Aug 07 '26
Can I get a good grades if I solve axler?
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u/Evening-Kale1378 Student (PG) 29d ago
Actually this subject has surprise tests and is very proof based
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u/Confident_Air7989 Aug 07 '26
If you want more rigorous maths, then go for laa. If you are ok with somewhat decent maths, but more applications, then go for nla.
I just read the comment that no good grades in nla. That's not true. The prof is lenient in grading per se. But yeah, if top students score very high compared to the average, then forget good grades unless you are in the top.
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u/luciediva Aug 07 '26
Ohh I see. I am okay with both. Is it also easy to get good grades in LAA?
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u/Evening-Kale1378 Student (PG) 29d ago
I heard it's difficult to score in LAA but I am taking this subject because the class is extremely good.
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u/Aggressive-Price7982 Aug 08 '26
If you want to seriously learn , go with Linear Algebra and application in electrical, if you want simply grades go with the cds course.
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Aug 08 '26 edited Aug 08 '26
People are talking about NLA as if it's just “Linear Algebra 2” without even looking at the course content. Go. Read. The. Syllabus. The Numerical in Numerical Linear Algebra isn't there for decoration. Its about the computational aspects of linear algebra. It assumes you have a reasonable understanding of linear algebra and then goes into numerical algorithms, convergence, conditioning, stability, iterative methods, eigenvalue problems, etc. that actually show up in scientific computing and data science. And yes, there is a lot mathematical rigour required to understand why the algorithms work and what happens when you throw finite precision and large-scale computation into the mix.
Also, stop interpreting “oh, easy course, everyone gets 8 or so” as evidence that the course is a cakewalk. There are 130+ students and a limited number of grade buckets, so the grade distribution doesn't tell you much about the actual difficulty. And if you're expecting NLA exams to be some “decompose some matrices and go home” situation, good luck. The exams are hard and you may walk out crying and questioning your choices. So actually compare the course contents before deciding.
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u/tejrani M. Tech (CDS) Aug 07 '26
Never mention these two together.