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Much deep learning focuses on image classification (the first topic of the fast.ai course) and natural language processing.

What is a good course that focuses on "tabular data", in particular predicting continuous outputs from continuous inputs, aka regression?

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It is not a full course but, since the fast.ai library does cover tabular data[1], they touch the subject in lesson 4[2].

[1]: https://docs.fast.ai/tabular.html

[2]: https://course.fast.ai/videos/?lesson=4

You might also be interested in the sister course to the one posted here: "Introduction to Machine Learning for Coders":

http://course18.fast.ai/ml

Just a question for a project of mine, but can tabular data be combined with NLP? Or should I train two seperate nets (i.e. with ulmfit) and try to combine the results?

You can one-hot encode categorical data like strings to build one big model. But if the data is independent, or if the tasks are orthogonal then you might be better served if you create two models.

I think most people would categorize that as machine learning or data science, not deep learning, maybe you would do better searching under those keywords

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