I’m kinda planning early and wanna do machine learning or AI later, maybe even research. Just curious…how do you choose the right ML/AI stuff if you’re doing your MS in CS at University of Florida? like how should you plan your course selection so you don’t mess it up later?
Okay first off nice that you thinking about this now 
So at University of Florida, their MS CS gives a lot of flexibility but it depends whether you do thesis or non-thesis. If ML/AI is your thing, definitely look at courses like CAP 6610 (Machine Learning), CAP 6411 (AI), and CAP 5510 (Bio-Inspired AI). Also they got deep learning and NLP electives too.
Just check if those need any pre-requirements like stats or python basics so you don’t get stuck later.
That’s a great question, and it’s smart to plan early if you’re thinking about getting into ML or AI during your MS in CS at UF. The best way to approach it is to start with core courses like Machine Learning, Artificial Intelligence, and Deep Learning to build a strong foundation. Alongside that, take supporting subjects like probability, statistics, linear algebra, and optimization, since they’re crucial for understanding ML theory. It also helps to explore what UF faculty are researching—look into AI-focused labs and consider reaching out to professors whose work interests you. When selecting electives, go for practical ones like Computer Vision, NLP, or Reinforcement Learning, as they give you hands-on experience in specific domains. Programming is key too, so be sure you’re comfortable with Python and libraries like PyTorch or TensorFlow. If you’re considering research or a PhD later, choosing the thesis option instead of coursework-only can give you deeper experience and help you build connections. Overall, mix core knowledge, useful electives, and research exposure to keep your options open and avoid regrets later.