I honestly felt that she was very dismissive. I felt very unsupported by her and my TA. I felt like I was treated as if I should have already known the material... except I thought this class was for people that have never coded before? Of course after lecture I would understand the concepts, but when it came to applying them to the homework, I often thought I needed a push or at least a similar example. When I would reach out, she would say to come to her in person instead of messaging her. However, there are only so many times I can call off from work or ask to switch shifts. When I would message her she would leave me on read for hours only to tell me again to go to office hours. Little did she know I was only able to attend my TA's office hours for the first few times.

Asking her about any code that she didn't write in her office hour will result in being told to ask the person who wrote it, not me. The person who only answered the code she written. The person who let you lose 5% of your total grade for computer compilation problems in one hw.

I feel like the past comments don't give her enough credit. I'm taking 3 other STEM classes this quarter with professors who are rated very high in Bruinwalk, but Prof.Keating is by far the most chill professor, and she makes this class very manageable. I really like her style of teaching - she just writes code during class, and we take notes by copying the code. I think this is better than using PPT because it makes the lecture better paced. Even though she doesn't give that many review materials, we do have a textbook containing exercises, and her exams are generally easy. She seems genuinely excited about the class material, and she can be helpful if you reach out. I hope I can take more classes in the future.

Professor Keating is an alright professor. I don't know how much of this is due to standardization of COMPTNG 10A, but a lot of the material was taught in a very bland, clinical manner that didn't help making learning some of the more difficult C++ concepts any easier. Otherwise, exams and homework were all pretty fair, if at times relatively difficult to figure out without any external help.

I enjoyed this class a lot more than PIC 10A, as I felt the content was more applicable and the graders weren't as nitpicky on coding style. The first half covered most of what we did in 10A (except in Python, of course) while the second half emphasized visualization and data science/machine learning.

The class was structured in a way that I believe allowed students to absorb the material well--everything was relatively easy to follow, and students had the chance to practice most (if not all) of the material learned outside of lecture. It definitely did amount to the workload of a 5-unit class, so expect to still put in effort. Professor Keating was, in my opinion, the best coding professor I've ever had. She explained everything relatively in-depth and structured her lectures into well-organized Jupyter notebooks. Homeworks were often challenging, but she and the TAs were pretty active on Campuswire to help students out. Exams were not too difficult, but you still need to study to get an A.

The machine learning project was fun but time-consuming. I sort of had to rely on machine learning knowledge from other classes for certain parts, but it was manageable. It was interesting moving through everything from exploratory analysis to modeling, and it wasn't too high stakes (~15% of our grade). However, I was slightly disappointed that (at least for our quarter) she didn't show us our grade on the project after posting the final grade. Because of this, I can't really say anything specific about how strictly it was graded, but I can say that it was a great way for us to apply introductory machine learning topics.

Really fun course. We got a little behind by the end which made the Penguin Project a lot harder than it probably should have been.
The homework assignments are super fun and challenging but I did most of them in one sitting. She uses Jupyter Notebooks which has proven to be the best lecture mode for these kind of coding classes.

Good course and extremely applicable to real life problems, we frequently used real data sets to model. If you didn't like PIC 10A, try 16A if you need additional coding experience.

This was one of the most fun classes I've taken in UCLA! Although I've had plenty of prior experience in Python, I still gained a lot from this class, especially in reinforcing concepts that I did not fully grasp previously. As Professor Keating's lecture notes were well-written, I stopped going for lectures after Week 2. Homework and discussion assignments were extremely fun to work on, as they often involved real-world applications of Python. Midterm was really easy with most of us completing it within 20 minutes, so she made the final slightly harder, but it was still manageable. The only downside was the project - my group put in a lot of effort into it, but perhaps we focused too much on the code rather than the explanations, so we were rather harshly deducted 20 marks for insufficient explanations, so do be wary of that.

I was searching for data science internships while taking PIC 16A, and it has been extremely helpful in tackling Python interview questions. I cannot stress enough how important the split-apply-combine technique we learnt for Pandas turned out to be. Now that I have secured an internship, looking back in hindsight, this class has played a pivotal role in my success. For anyone looking to enter the field of Data Science, I would highly recommend this class with Professor Keating.

This class was easy to follow, and if you put in the effort, you will get an A. It seems most of the reviewers here did not go to class.

Overall, I liked PIC 16A much more than PIC 10A. The content was not overly difficult and felt more applicable. Professor Keating is a very nice person, and definitely cares about ensuring that her students understand everything.

Contrary to some of the other reviews, I really enjoyed taking this class with this professor. I'm currently taking PIC16A with her because I appreciated her way of teaching that much. Her lectures are efficient and understandable, and she posts the code in case you miss class. The homework can be difficult, but they are definitely doable and related to the class content. The exams definitely can be tricky but still fair and based off the content you learn in class. She also gives you a double-sided page of cheat sheet. I had a medical emergency this quarter, and she gave me a VERY gracious extension which was incredibly appreciated. I would take any other PIC class offered by her if I could.