Quantum Computing

Pros:

• Provides a good overview of quantum computing
• Course is recent enough (2022?)
• Textbook chosen by the course is a very thorough one; reading it will teach you rigorous understanding of basic quantum computing concepts.

Cons:

• Sorry but for the first half of the course, the lectures were nearly useless for me. The first half of the course was very math heavy, but the lectures do not go into nearly as much depth as necessary to understand the math. So for the first half, the course was just about reading the textbook and doing assignments.
• The second half of the course was way too shallow; it goes over a few topics (routing, error correction, qaoa, etc.) but not to any sufficient depth. I totally coasted through this half of the course, spending <1hr per week, and felt like I learned very little.
• The labs are very shallow as well. The code I had to write was way shorter than the instructions, and much of the time was spent on understanding what exactly the lab description wanted, because the specifications weren't precise. And because of that, I had to trial&error with the autograder to see if what I wrote conformed to the intended specs.
• When they grade the problem sets and exams, they tell you what you got wrong, but they don't tell you the correct answer. I cannot understand why.
• Problem sets and exams are all numeric answer or multiple-choice questions. There was not a single question that required a human to grade. The quality of the exam questions were poor - imo they did not accurately assess actual knowledge (btw I got above 90% on midterm so I'm not saying this because I'm salty or something.) I really think requiring some open-ended answers should be necessary to bring up the exam quality.
• Despite the problem sets, labs, and exams being completely auto-grade-able, it takes weeks for them to be graded somehow.

Overall, my recommendation is, if you want to learn quantum computing, just grab this course's recommended textbook, read through it carefully, do the exercises on it, you'll be good to go.

I really liked this class. The front-half of the course was how quantum computing and algorithms work in theory, and the second half focused on current research implementations. The math is heavier earlier on but not overwhelming, especially if you come from an engineering or math background. Familiarize yourself with bra-ket notation and matrix operations/general linear algebra beforehand. Otherwise, I think you can pick up on the math you need during the course. Others have noted that the instructions aren't always clear in assignments. This lack of feedback on GS and the instructions can be very frustrating, but I would say the majority of the assignments are clear enough or have been addressed on ed discussion pages. Overall I think this class is worthwhile if you're at all interested by quantum theory or enjoy learning about some niche corner of computing systems.

Idk who said that this course was easy, but trust me it is not. It was my first omscs course and coming from a very heavy math background I thought it'd be easy. Well I didn't take into account that assignments have little to no instructions other then bang your head against the wall, and I also I had no idea that exams were not at all what assignments were.

I feel like between exams and projects I was doing 2 different classes. Apparently in non-summer semesters they had homework problems, but they refused to share it with us. I think that did us a big disservice.

Yes you have unlimited attempts on the quizzes and also paper reviews are an easy 4-5/5 points. But this class was far from easy or clear.

If you are not a great test taker, skip this course. I had 100% on all assignments, but ended up with high B because midterm and final are 20% each of the overall grade.

I got As in much more difficult courses like Distributed Computing. Exam weight distribution is killing the joy out of this course. I think I would prefer having tougher assignments with more weight and more forgiving exam weights. Labs and KCs are very easy. Those can be hardened up in favor of lesser exam weights.

There are practice exams where you can earn +5 points for your midterm and +10 points for your final if you score 80% or higher in practice exams. The system of awarding bonus points is a reflection of bad exam weights IMHO.

Just took final, expected to receive an A.

To do well in this course one has to really grasp tensor networks which is essentially what a quantum circuit is. Spend time in the first half of the course intensively getting comfortable with tensor products, bra-ket notation, constructing larger gates by hand, and proving equivalency in gate operations etc. Comfort with these basic aspects will greatly aid in your midterm, and general understanding of applied materials in the second half.

The topics presented were quite interesting that it was really easy to do extra work just to read up on the latest advances outside of what was presented in the class.

Overall, a great class, BUT you need to invest the time to grasp the mathematical foundations of quantum circuits in the first half. You will need strong foundations in linear algebra, complex numbers and some basic algorithms understanding.

Took it in Spring 2024.
Overall, very good course.

Pros:

1. Good coverage of all quantum computing topics.
2. Labs and problems are tightly connected with the course material.
3. Fair exams provide good coverage of all material across all modules. They are challenging; you must thoroughly understand all homework questions.

Cons: Lectures are too concise. For the first half of the course, you are required to read the textbook. (Thomas Wong's book is actually much better.) It tooks much more time (~ 20 hours) for the first half. The second half tooks much less time (~ 8 hours )

TAs: I don't want to blame them, but they are often unhelpful in answering questions related to the course materials, and their answers can be more confusing. This is completely different from the Head TA of HPCA (Nolan is great).

In conclusion, it is a great course with relatively new materials and good coverage of all topics. The TAs are very responsive. They are helpful in terms of learning, but they answer logistical questions promptly.