COMPTNG 16B
Python with Applications II
Description: Lecture, three hours; discussion, two hours. Requisite: course 16A or equivalent. In-depth application of Python programming language to problems arising in variety of areas of current interest such as machine learning, computer vision, statistical analysis, numerical analysis, and data acquisition. Advanced Python programming techniques to improve computational efficiency. P/NP or letter grading.
Units: 5.0
Units: 5.0
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Most Helpful Review
Spring 2021 - 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.
Spring 2021 - 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.
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Most Helpful Review
Winter 2024 - He was a good professor, always ready to help and responsive to emails. The first couple homeworks were kinda hard, but he was available in office hours. Attendance is mandatory for lecture and discussion, as they randomly give quizzes to check. The quizzes are easy and marked for completion. This professor emphasizes the math behind ML stuff, so be ready for that. It's not a huge deal if you don't come from a math background, but the beginning stuff might be confusing. Prof and TA are there to help though!
Winter 2024 - He was a good professor, always ready to help and responsive to emails. The first couple homeworks were kinda hard, but he was available in office hours. Attendance is mandatory for lecture and discussion, as they randomly give quizzes to check. The quizzes are easy and marked for completion. This professor emphasizes the math behind ML stuff, so be ready for that. It's not a huge deal if you don't come from a math background, but the beginning stuff might be confusing. Prof and TA are there to help though!
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