If you are deciding between professors for PIC16A, Phil should be your choice. He cares so much about his students - both in whether you're grasping concepts and actually learning and in your mental health. His emphasis was not on grades but more on actually learning the material - he drops your 2 lowest homework grades, 4 discussion grades (which you complete with the same group of one to two people through the whole quarter), and 5 quiz grades. So if you're not doing too hot one week, don't stress.

I came into the course not too confident in my coding skills (I only took one PIC class before this) but I had all the resources I needed to get through this class. Challenging, but not to the point of insane stress. I really liked the final project we did surrounding data science and machine learning - you complete this project by week 10 and is done with the same group from your discussion. I like that the project was based on the students' interests that were surveyed at the beginning of the quarter. It seemed like a lot when we were first introduced to it but a lot of the work for the project is done in discussion and through homework already.

Campuswire was a huge helper for me in the class to ask questions about homework or other general questions. You could receive up to 2% extra credit from posting thoughtful questions and answers on there, and up to 3% through a short essay surrounding equity, justice, and algorithms.

Phil was always available and open for questions. He held office hours at normal hours and also later in the evening to accommodate for students in different time zones. If you emailed him he'd reply quite quickly and always obviously took time to respond thoughtfully. He also checked CampusWire frequently for questions to answer that other students couldn't answer.

The midterm and final did take much longer for me than the estimated time given, but I feel this is common for all 24hr tests at this point. He even emailed us after the final saying that he has heard this concern and would take that into consideration while grading (what a gem), and had a whole extra part on the final to explain your progress through this class as a way to give him more insight into you when he considers your final grade.

If you do take this class with Phil (which you should if you want to learn in a really engaging way), make sure to ask him for his memes.

AMAZING
This was Phil's first quarter teaching at UCLA and I can already rate him as one of the BEST professors I've had in my time here. He's very funny, accommodating, and clear. Class was cancelled on election day 2020 in case students were feeling stressed.
I came into the class with no python coding experience and finished knowing so much. Phil makes the material very simple to understand with intuitive and stylish lecture notes.

The only negative standing out was that the final was hard, but I wouldn't worry about that too much if planning to enroll with him in the future. This is because Phil seems to be constantly gauging student's learning and success with the material, and making changes that will only benefit students.

HIGHLY RECOMMEND

Amazing class with an amazing professor. This was one of the most useful classes I've taken at UCLA. Dr. Chodrow is funny, kind, always available to help, organized and very knowledgable. I was in a different time zone and never felt like I was excluded even though my learning was asynchronous. The assignments can sometimes require a bit of thinking but I guess that's what learning is. He uses Campuswire and highkey that's a really useful resource to ask for help from classmates and him. We learn about basic Python language + natural language processing + machine learning. We also did a mini project on data science but he tailors that to fit the interest of the class. Pretty beginner-friendly, would recommend Dr. Chodrow and this class 100%.

Breakdown of Grading:
- 20%: Participation
- 20% Homeworks
- 10% Quizzes
- 10% Mini Project
- 15% Midterm
- 25% Final
(+ 3% extra credit from asking good question and/or writing an essay about algorithms and social justice)

He is a gifted teacher and a gem of a person. Take his class, it might be challenging and work intensive, but you will learn a LOT.

Professor Chodrow is awesome! He expects a lot from his students but his exams and Homeworks are very fair.

Like the other commenter mentioned he gives extra credit for a bunch of things in case you fall behind. He's also extremely responsive and it seems like he devotes a lot of time to preparing class content and lecturing (more than any other professor I've ever had).

Would recommend him 10/10 if you want a good grasp of Python

Professor Chodrow is amazing - his lectures are engaging and clear, he devotes a lot of time to being able to help students outside of class and genuinely cares about his students learning, and his homeworks and tests are fair. The class (during COVID) was structured as a flipped classroom so we had asynchronous lectures every MWF and a quiz on them due at midnight each of those days, but there was an optional live lecture on those days as well. The quizzes were only a few questions and help you to not fall behind. On TR we had discussions where we worked in groups (the same group for the whole quarter) to complete worksheets which really helped show if I was confused on a certain topic. During discussion the TA, professor, and LAs come through to check and see how you are doing and help you if you are stuck. The groups are really helpful since you get to know 1-2 students in the class and can go to them for help studying or if you get stuck on the homework. This is also your group for the mini project due at the end of week 10. The grading scheme gives a fair amount of dropped scores (2 of 8 homeworks, 7 of 27 quizzes, and 5 of 19 discussions) so if you couldn't attend or had a difficult situation it you're still able to do well even if you miss some stuff. There's extra credit offered for insightful questions on campuswire or a short paper on algorithms, equity, and justice. Prof Chodrow is one of the best professors (if not the best) I've had at my time here at UCLA and I would definitely recommend taking this class with him.

I think the structure of the class is PERFECT for most, especially if you're only starting to get into programming and you need a class that will make you feel more confident in yourself as a programmer.

Professor Chodrow makes sure that the students stay engaged with the material throughout the quarter, but not to the point where he overloads you with work.

If you have the opportunity to take this class with him, DO IT!

I took this class as an intro to python in preparation for python-based CS & EE courses, and it definitely was the move. The class atmosphere is super positive and there's none of the stress/competitiveness of CS 31/32. Its all about individual growth and learning. The notes are also an amazing resource for future classes. It's very chill and you learn the ins and outs of python, numpy, pandas, and sklearn.
I would take this class again with Prof. Chodrow, it has made my life much easier in other classes, and I no longer need to learn python on the fly every time I need to use it.

Professor was very accommodating. Had cool homework and projects. The tests and quizzes are not hard at all. I would recommend taking a look at the syllabus he already has posted on his website probably if you are interested in what topics are taught in this class as it seems PIC 16A seems to differ based on the professor teaching it. I generally hated working in groups for discussions though and on the final project. If you hate group work maybe reconsider but otherwise, I have no complaints.

Great class, even better professor!

Dr. Chodrow spends so much time carefully creating worksheets that are both engaging and informative. PIC 16B really gets you accustomed to TensorFlow and other intermediate/advanced Python libraries. Homeworks are challenging but super fun to do. I would not hesitate to take a class taught by Dr. Chodrow again. Easily the best professor I've had during my time at UCLA.