[D] Could really use some guidance . I'm a 2nd year Data Science UG Student

I'm currently finishing up my second year of a three year Bachelor of Data Science degree. I've got the basics down quite well, linear regression, logistic regression, decision trees, (not knowledgable about neural networks/nlp though) I'm comfortable with Python, pandas, sklearn, and I plan to start learning PyTorch/Keras(whichever might be better). I also know SQL at a decent level.

But I feel a bit lost on what to do next. There's so much material out there and deciding a source to learn from gets confusing. I've seen people mention fast.ai, Andrew Ng's courses, Kaggle competitions, building projects, and I genuinely don't know what order makes sense or what's actually worth my time. Any help is GREATLY appreciated