UCLA or UC Berkeley? Time Sensitive!

[pl82524]

@firmament2x

@pl82524 . . . just as a point of clarification, Applied Math isn’t attached to the Data Theory major; it’s a standalone major.

Here’s what Professor Miles Chen said about the Data Theory major for future reference, with a datestamp of around middle part of 2019, and I’m sure (I hope!) he won’t mind as I’m just someone who wants to disseminate information about the major:

The major is jointly administered by the Math Department and Statistics Department. The goal is to provide a strong foundation for students who plan on pursuing graduate studies in fields related to Data Science.

Students will have to take statistics courses that cover data analysis (Stats 101A, 101C, 102A, 102B) as well as courses that cover more advanced proof-based math like Math 115A and Math 131A. Students will learn programming in C++ (Pic 10A), R (Stats 20), and Python (Stats 21 - new course). It is a capstone major, so students will take a capstone course with a data project in their final year. A few new courses are also being developed for the major. The full requirements for completing the major is expected to be published and made public by Fall 2019.

There’s a few reasons for the naming “Data Theory” rather than Data Science. Data Science rests on a foundation of math, statistics, and computer science (in addition to domain knowledge of the source of data). One could imagine another major with a stronger focus on software/computer engineering that is developed as a joint venture between Stats/CS or Math/CS departments. “Data Theory” highlights the more theoretical components of the major. That said, students in the data theory major will still get a lot of exposure to computer programming - but will probably learn less of the theoretical aspects of computer science (similar to the difference between PIC courses and CS courses.)

Edit: And all the best at UCB.

Thank you very much for the clarification!