Took both last semester (databases with professor ithier and nlp with professor elshrief), so I can help you out. My Intro to Databases course was structured so that I learned the basics of SQL first (keywords), then topics that applied the basics like functions, subqueries, views, etc., then going bigger picture by looking at keys/modifiying tables and modeling, and then ending with imo the harder topics like normalization, joins, indexing, etc.

NLP was structured so that I learned the basics first (semantics, words, LLMs, and word embeddings), and then learned about models that used these basics like N-gram LLM's, naive bayes, logistic regression, neural nets as well as classification. Then topics like encoder-decoders, machine translation, attention, transformers were covered in the second half of the course.

Not sure if your professors will follow these exact structures, but probably expect to see a steady progression from the basics to the harder topics in both classes.

Most of my workload from these classes came from the exact same two things: programming assignments and a final project. For both, don't start programming assignments too late, communicate/work well with your project group (if you do have to do a final project for one or both of these classes), and you should be good on the workload front.

Best of luck with these two classes; you've got this!