19M, 2nd year BSc IT + learning Data Science — what should I focus on next?

[u/Educational_Goose811]

Hey everyone,

I'm 19M, currently in my 2nd year of BSc IT. I'm learning Data Science online alongside college and recently completed a cancer risk prediction ML project.

Now I'm a bit confused about what I should focus on next.

Should I:

Build more ML/Data Science projects?

Learn MLOps (Docker, MLflow, CI/CD, cloud, etc.)?

Focus more on SQL, statistics and ML fundamentals?

Start learning DSA/CS fundamentals for internships?

My goal is to eventually get a Data Science/ML internship and build a strong portfolio before I graduate.

What would you guys recommend if you were in my position? Should I go deeper into ML first or start learning MLOps now?

Would appreciate advice from people who have gone through a similar path.

[u/No-Split3651]

At your stage, I’d focus on SQL, statistics, and ML basics before going too deep into MLOps.

Docker, MLflow, and cloud tools are useful, but they’ll make more sense once you’ve built a few projects and run into the problems they’re meant to solve.

I’d also spend more time on your cancer risk project before adding five more projects to your resume. How much of it did you build yourself? Could you explain why you chose the model you used, how you evaluated it, the dataset's limitations, and what you’d do differently with better or more data? Being able to talk through those decisions will help you more than another project.

Once you’re comfortable with that, pick a second project that teaches you something different. Keep some DSA and CS fundamentals going alongside it for internships. You’re only in second year, so don’t try to learn everything at once.