Q: I’m on the waitlist . Will I be able to get off the waitlist?

We are now past the CMU course add deadline. Sorry that we weren’t able to fit everyone into this course. Hopefully, we’ll be able to see you in a future offering of the course!

Q: When will this course be offered again?

A: Hopefully, in Fall 2022, but we’re not sure at this point.

Q: What is the situation will all the different course numbers 15-388 and 15-688?

A: 15-388 is an undergraduate version of the course, whereas 15-688 is a graduate version. The lectures for the two courses are the same, and the only difference is that 688 has an additional programming question on each homework assignment. This results in the 688 version being 12 units, rather than the 9 units for 388.

Q: Can I switch between 15-388 and 15-688?

A: No, sorry. Undergrads will take 388 and grad students will take 688. If you are in 388, you are still welcome to do the additional 688 homework problems, they just wont count toward your homework score.

Q: Can I take the course pass/fail?

A: That is up to you and your academic advisor / program administrator.

Q: Can I audit the course?

A: No, sorry, we do not do formal audits for this course.

Q: Will this course focus mainly on applying techniques from existing libraries to practical data science problems, or writing the underlying algorithms from scratch?

A: Both, to a certain extent. There will be plenty of focus on applying algorithms (often best used through existing libraries) to practical problems, but these libraries can be used more effectively when you understand the underlying algorithms well enough to implement them yourself. So, at least for the more straightforward algorithms that we cover, you will be implementing these yourselves. The 688 level course assignment will do a bit more of this underlying implementation than the 388 level course.

Q: What is the difference between this course at 10-301/10-601/10-701/15-281/etc?

There is naturally some overlap between this course and various machine learning or AI courses taught at CMU. There are also several courses taught outside of SCS (in Stats, Heinz, etc) that have similar topics. The short answer to this question is that the focus of this course (e.g., in the assignments) is more on programming and analyzing data, and much less on the math than in most courses we’re aware of. However, the best way to get a sense of the differences is to simply compare the lectures and assignments.

Q: I have a question that wasn’t asked here.

A: Come to office hours, or ask on the course forum.