Taught by: Philippe Raynal
Content (Structure/Organization): 3
Topics:
Classical computation (Week 1-3)
Linear Algebra (Week 3-6)
Quantum circuits and measurement (Week 8-10)
Algorithms (Week 11-13)
Assessment breakdown:
Participation (7%)
Tutorial submission (8% graded for completion and not correctness)
Midterm (20%)
Essay 1 (20%)
Essay 2 (20%)
Group Project (25%)
The content is roughly based on the foundational chapters of Nielsen and Chuang's canonical textbook "Quantum Computation and Quantum Information", but since this is an NUSC course there is quite a bit of simplification and many things are glossed over. I was a bit disappointed that we only really started on quantum in the second half of the semester, but I guess the idea was that the first 6 weeks' worth of background was necessary as preparation for that. Additionally, we ended up barely touching on algorithms, as prof only went through one of them (Deutsch's algorithm) in class. The rest were left for us to learn about from the group project, as each group had to select one algorithm and explain it to the rest of the class in a presentation.
For the assessments, I didn't really like the essays, and frankly would have preferred to just have a midterm and final, or perhaps another group project. This is because the essay topics were really weird - the first one was on whether computers can ever understand things, and the second was on whether the universe can be considered a quantum computer. These are interesting as shower thoughts but rather difficult to write about as a graded assignment - for the first, because "understand" is ill-defined in the literature, and for the second, because I do not know (and did not learn in the course) enough about the universe to write anything of substance. As such, each essay I wrote ended up being 3000+ words of pure yappanese (longer than my NTW final submission btw).
Manageability of Workload: 4
The workload was light for me, but only because I had learn[ed] quite a lot of the pre-midterm content before, which meant I didn't have to spend that much time doing the tutorials. The essays did take quite a bit of time (since they were quite long), but the group project was also not too heavy since we only had to do an oral presentation (no report to be written).
Ease/Difficulty of Attaining Grades:
The grade distribution is probably similar to that of other NUSC courses (i.e. most people get B+/A-), at least for the essays and group projects. As such, I think the midterm may be a significant differentiating factor even though it's only 20%.
A brief comment on the essays - as I mentioned above the topics are kinda weird, but prof seems to really like it if you engage with them in the affirmative even if you think it doesn't really make sense (i.e. computers can understand, the universe can be considered a quantum computer). So make of that what you will :)
Learning Value/Recommendation: 3
I would say the course struggles a bit to decide who it should be catered for - if you have no background, it may be a bit too difficult, but if you do have some background, it may be too basic. Nevertheless, for me personally, I think I appreciated having some exposure to the field without having to expend too much effort, and if I do find myself interested in learning this stuff in the future[,] I am definitely better positioned to continue reading the rest of Nielsen and Chuang than if I hadn't taken the course.
That being said, quantum computing is a blossoming field and it's probably worth picking up some of the basics (especially if you know some CS/math/physics already). I will also say that despite my gripes with the course, it's definitely still better than most of the science courses that NUSC offers based on what I've taken and heard from others (ahem NSS)
About the Instructor:
Dr Raynal is clearly both knowledgeable and passionate about the subject. I think he's ok at explaining things, and always open to questions during/after class. This is important because he sometimes goes through things too quickly (which in fairness to him, is probably because it's hard to judge the background of the class). Some people also like to complain that he isn't rigorous enough, but frankly I think this is fine since the point of the course (being an NUSC one after all) is to get some sort of big picture without going too deep into mathematical formalisms. It's not as if he doesn't know, and he's willing to entertain questions about such things after class.
Content (Structure/Organization): 4
Course content is clearly laid out, and covers three parts: Classical Computation, Linear Algebra, and Quantum Computing.
Assessment comprises two essays, a group presentation, weekly tutorials, and a midterm exam.
Accessibility and Assessment: 3
Prof Raynal does a good job in introducing the class to the concepts, but despite that it may be difficult for students from a non-computing background to do well at first. The content may also be a lot more technical than non-STEM students are used to, which may create difficulties in the latter half of the sem when linear algebra concepts are a mainstay.
Manageability of Workload: 3
On par with most NUSC courses, although non-computing and non-STEM students may need more time for the weekly tutorials or to pick up new concepts.
Ease/Difficulty of Attaining Grades:
Despite struggling in the first half of the sem (averaging a B to B+), I ended up with an A-, so it is possible to pick up the load in the latter half of the sem.
Learning Value/Recommendation: 3
While not relevant to my major, it was very interesting and worth learning.
About the Instructor:
Prof Raynal is very knowledgeable in the course's subject domain, and can communicate it to students well.
Name: Gautham Kailash (@kailashgautham)
Content (Structure/Organization): 5
Course is very well structured, albeit fairly high level - a strong computing and mathematics background would be advised before taking this course. Starts from classical computation and follows a relatively structured flow into gates, quantum gates, and then quantum circuits. Students definitely need to put in some effort outside of class to keep up.
Accessibility and Assessment: 2
Not too accessible (this might be because 90% of our class had a computing background so Prof could go faster. He did mention that if there were non-computing students he'd slow the pace down to help them get the concepts down. Regardless, the subject matter is quite heavy).
Manageability of Workload: 2
Quite heavy workload. One midterm exam (math and computation concepts), weekly tutorials (graded), midterm essay (10 pages single spaced font size 10), final essay (same specifications as the midterm), 30 minute group project presentation.
Probably one of the heavier NUSC courses I've done so far.
Ease/Difficulty of Attaining Grades:
I think that as long as you put in effort and Prof can see that, you're probably getting an A-. A is probably reserved for exceptional essays and very consistent overall performance.
Learning Value/Recommendation: 5
4 out of 5. Not sure if I'd use this in my work, but nonetheless something important to move as the world progresses quickly into using quantum computers.
About the Instructor:
Prof is extremely knowledgable, and if you go in with an open mind you can really learn a lot from him. Admittedly I started losing him in the latter parts of the semester like week 10 onwards, but that's more because my math fundamentals weren't the best and I was dying in other courses so I couldn't focus as much time and energy on NST.
Prof Raynal is very passionate about quantum computation and really cares about our learning experience, and has at many times explained even simple concepts to us after class. Basically he won't judge you if you're lost and is instead (I like to think) happy that you're trying to learn and understand. He teaches quite well and can convey the information that he needs to.
Additional Comments/Word of Advice:
If you do not have a strong STEM background or if you do not have some basis in courses like CS1231S / MA1100 / linear algebra, I'd recommend against doing this course. But if you're willing to keep up with some fairly complicated mathematics, the learning potential is really high.