I'm currently pursuing a Master's in Data Science, but I don't have any prior experience. I started with RStudio for my first couple of courses, and while I pushed myself to apply what I learned in both work and school projects, I've found that two short classes (each lasting 7.5 weeks) just didn't give me enough depth. My next courses focused on Python basics and SQL, and I passed them, but I felt panicked the whole time and nothing seems to stick. Now, I'm struggling to start using Python properly and I feel stuck. I worry that despite my good grades, I'm not actually learning enough, and I feel like I've lost my momentum by not applying Python at work yet. It's making me feel trapped and fraudulent.
1 Answer
Python is a fantastic language for data science! Think of it like playing with Lego—there's so much you can create by mixing and matching. If you're doing data science, I suggest you start simple. Maybe build a basic API to serve one of your models using FastAPI and gradually add features, like validating your model with production data, setting up alerts, and automating the generation of new candidate models. You can do a lot with common libraries and not a ton of code. Just remember to keep it straightforward as you learn!
This is really solid advice! I appreciate the encouragement.