SC1004 LINEAR ALGEBRA FOR COMPUTING (3.0 AU)

This course aims to support you to learn mathematical concepts related to linear algebra. You will develop set of mathematical skills for applications in computer science and engineering,
e.g., machine learning, computer graphics, data science etc.

Easiness of Content

90%

Manageability of Workload

100%

Quality of Teaching

60%

By 01 reviewer(s)

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  • painge

    painge

    Took this module in 21/22 Sem 2.

    Components: 2 x 40% Midterm + Final quiz and 2 x 10% Take-home assignments

    First half was taught by Prof Lana. There are pre-recorded lectures. Do watch them before the live lectures as she mostly recaps the content and then solve some questions live. Accent is quite thick but it is okay for me. Content taught are linear systems, linear independence, matrix operations, computing (up to 3×3) and applications of determinants, spaces, subspaces, transformation matrices. Did not really attend much of the live lectures, but caught up with the pre-recorded ones. Please make sure you understand this half properly as the concepts are assumed knowledge for the second half.

    Second half was taught by Prof Tay KB. No pre-recorded lectures this time, content is taught live. Although, lectures are recorded and disseminated after the session. Tends to read off the slides, but the content in the slides are informative and adequate enough in my opinion. Content taught are orthogonality, Gram-Schidmt process, least squares, eigenvalues, eigenvectors and diagonalisation. The pace for this half was pretty fast, as there are a lot of content to cover in a short time. Most of the content from the slides and tutorials are taken straight from = 30 should be safe.

    Quiz 2: Second quiz consists of T/F, fill in blanks, computation and proving questions. The time crunch was overwhelming in the second quiz as there are 18 questions to be done in 50minutes, and some of the questions included tedious GS orthogonalisating. It was also easy to overwrite proofs for some of the questions. Performance and grades for this test wasn’t released, but from Prof Tay’s remarks, it seemed bad.

    Take-home test 1: Short problem set to be done over the weekend. Pretty straightforward and ample time was provided to finish and submit. Open everything so you can discuss with your peers or consult stackexchange if you wish.

    Take-home test 2: Lots of controversy for this one. Prof Tay did not want the test to be done over the weekend as it was too long for him. He also did not want collusion or plagiarism for an open everything assignment…. Thus, he set a Saturday morning for us to finish and submit within 2.5hr. This was pushed forward to the next day night (Sunday) due to Ramadan and part-time students being unable to attend on Saturday. The questions were pretty tedious and long, and took up much of the 2.5hrs. It felt more like a final than a take-home assignment LOL. Open everything was allowed, so discussion with peers was encouraged. Personally, I understand his rationale, but all this hassle and inconvenience for a 10% assignment just isn’t worth it IMO.

    Overall: Ensure you practice often using the tutorials, extra practices or textbook. Most computations should be done naturally and quickly. Useful module for future machine learning or computing graphics in the future.

    May 8, 2022
  • painge

    nhj

    Took in AY21/22 S2. Most of the module was adapted from Lay’s

    May 7, 2022

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Easiness of Content
Manageability of Workload
Quality of Teaching