FiveRingsTrading

I graduated early with a CS degree from a state school and worked in medical robotics and aerospace as an embedded software engineer during undergrad. My background is mostly in machine learning and math, and I wanted to pursue a technical master’s in AI. I ended up missing the application deadline for the AI program at my school and enrolled in their Data Science MS instead. Based on the course descriptions, I expected a fairly technical program focused on statistical methods, ML, and building complex data pipelines. Unfortunately, the program has been much less rigorous than I expected. The most “advanced” stats class feels comparable to an undergrad intro stats course, and the programming/data pipeline classes are mostly basic Pandas and high-level tooling. I’m now two semesters into the program and feeling pretty unfulfilled. I also have two quant internship/full-time offers contingent on me finishing a master’s degree, and I’ve already paid a lot out of pocket. Has anyone else been in a situation like this? Is it worth trying to switch programs this late, or is it better to just finish the degree and focus on self-studying the technical material I actually want to learn? Do employers care much if those skills come from self-study rather than coursework?