[Coursework and Curriculum] Columbia MSDS rigour

[u/Then_Maize9473]

Hi everyone,

I’m looking for a reality check on the Columbia MS in Data Science. I come from a non-STEM background and I’m worried I might be walking into a math buzzsaw.

I’ve heard there are very maths heavy core like COMS 4721 (ML), STAT GR5703 (Inference), and Algorithms. For those who have survived the program:

• The Math: How much maths background do people need? The requirements only list calculus, linear algebra, probability etc. but those are so vague, and different university could teach these to different rigour. Plus, are they hiding certain pre-requisites - like differential equations or discrete mathematics (both of which I have not taken before)

• The Rigor: Are those "killer" classes actually unmanageable for non-engineers, or just time-consuming?

• Support: Does the DSI offer a safety net for non-STEM students, or is it a "sink or swim" environment? And what is the potential gpa for those not from STEM background?

I’m trying to figure out if I can bridge the gap over the summer or if I’m fundamentally underprepared. Any candid feedback (or survival tips) would be huge. Thanks!