Reviews

Pros: 1. relevant topics 2. accessible lectures 3. Cons: 1. 2. 3. Detailed Review: Great class. Totally worthwhile. Teaches a bunch of advanced topics in the computation of Linear Algebra constructs, like matrix decompositions and eigenvalues. The lectures were very accessible, and the professors were very responsive. However, they are retiring after Spring 2021, so it's unclear if the class will continue. I hope it does, as the material touches on so many other classes in the program, like Optimization and Quantum Computing. The website they put together serves as a sort of textbook, and as such is extremely useful and informative.

Pros: 1. Gives a lot of Android knowledge and make you good at it 2. Professor is very understanding 3. TAs are helpful and generous Cons: 1. Some assignments materials are not covered in lectures Detailed Review: Emmett is the coolest professor I've ever seen. What makes him different than other professor is that he is very active on Piazza. He blends in very well with his student despite the age gap. He explained the lecture and assignment very clearly. The TAs are helpful and generous. You will learn a lot in this class, especially if you're not an Android developer.

I enjoyed all the material in this course. The information contained is designed in a way it's practical but it does not leave theory behind. In the end you are ready to start implementing the knowledge obtained into personal projects. The teacher is very considerate and the homework and projects are very interesting and exciting. I would take this course again.

Pros: 1. Professor involved 2. Instructions were straightforward 3. Cons: 1. Some videos are outdated 2. 3. Detailed Review: For me, this is the best course that I have taken in this program. The videos were quite helpful and the expectation was clear on the pdf instruction. There were lots of hints on the codebase and the Instructor posted some new videos to update older ones. Although, I spent lots of hours on the HomeWorks but it was worth it since I had to do a lot of debugging.

Love the lectures and love how practical the course is, although I wish the course could focus a little more on the theory and also more on advanced models. Homeworks take a great amount of time to implement and take a lot more time to tune. Final project is super frustrating. Only a small portion of the final project is deep learning related, the other part is just to make the controller work, which is a very frustrating and time consuming. TA is amazing. I think one of the TAs for this class is probably the best TA I've had for any classes.

Pros: 1. Interesting material 2. Cutting edge 3. Responsive TAs Cons: 1. programming projects were a nightmare 2. Quizzes were very stressful 3. Detailed Review: The content of this class was really cool. The lectures were good, but often made huge leaps, especially in the later half of the class. The quizzes were stressful, since you get 1 try on each question, and they were often puzzling and somewhat ambiguous. There were so many questions about the meaning of the quiz questions that the TA’s gave up answering questions after a while. In the end, the cutoff for an A was only 88% and there was a curve, so it was even less than that. This class put me through the wringer, but I got a good grade in the end and learned a lot. The first programming project was a mess, and they had to grant credit for just doing your best on it. I assume they will have fixed that in future iterations of the class. Expect to be tortured, but expect to learn a lot.

I would simply watch the lectures (3 hrs per week) and not do anything else. Then, I would spend/binge around 40 hours over the course of 2-3 days doing the projects. Once you decipher the assignment (sometimes they were worded poorly and hard to understand) and figure out what lectures the project correspond to, the projects would become really easy, just REALLY long to code up because there was so much you had to do. The Rust2PC project (project 4) sucked for me personally. Project 5 was probably the most time consuming, yet the most interesting of them all.

If you have good background in OS you will learn so much from this class. Even for those without OS background, it is not difficult to ramp-up quickly. Totally worth it!

Pros: 1. Amazing professor and lectures 2. Very good lecture summary notes 3. Great recitation and homework problems Cons: 1. Homeworks are extremely hard 2. Office hours are limited compared to the content 3. Hard exams with no curve Detailed Review: This course is an amazing course on the topic of basic Quantum mechanics and computing. Professor Aaronson is simply an amazing Professor who explains the concepts very well. The concepts themselves are difficult to grasp for first-timers specially after the midterm, but the professor still does a great job. The TAs are also very knowledgable as they are PhD students in the Quantum field. Homeworks and recitation notes enforce learning and the "textbook" helps to explain key points. The issue that some may face is how math heavy this course is. I personally had math background but still needed to refresh as the concepts require math knowledge. Most importantly you should to be comfortable with Linear Algebra, probability, complex numbers, and some computer complexity concepts. The homeworks take a lot of time as they are very difficult. You need hours of office hours and restudying to understand and solve the problems. There are some recitation problems to help you, but other than that you're on your own. Every week, there's a new homework and it becomes a marathon. Also due to the number of students, the office hours are always packed with people jumping over your questions. This is expected for a difficult online course, and this course would definitely be better in person. The final note is that the two exams (midterm and final) are difficult. They are a bit easier than the homeworks, but the time is limited. You need some creativity and a deep knowledge to be able to get a good grade. Also, there is no curve, meaning that if you get a grade, that is your final grade. That's where this class becomes stressful and a bit tough compared to other courses in this program. With all that being said, I really enjoyed this learning experience, and regardless of the grade I got, I feel like I learned a lot more than some other classes which I got an A in. Definitely one of the best courses in this program if not the best one. You should definitely take it if you are interested!

This course is "straightforward" but not "easy", in the same way that climbing a mountain is straightforward (just keep moving upwards) but not easy. The course requires quite a lot of effort to really dig deep into the topic. For every week, I required ~15-20 hours of work to complete all the videos, homeworks, and the weekly assignment. It is worth it though; the course content is arranged excellently (I did not once go beyond 20 hours per week, and rarely needed to Google terms). The instructors, Maggie and Robert, are about the nicest professors ever: the deadlines are flexible, and they focus on learning more than submissions and grades. They are masters of their subject (numerical linear algebra) and are very active on edx for doubts. Overall 5/5; one of the best courses I have taken in terms of content and probably THE best course in terms of instructors.