[fantispug]

This may make sense if you want to do image processing and deep reinforcement learning. But there are lots of other domains.

For tabular data (which is probably most relevant in Pharma, and probably the best place to start) Introduction to Statistical Learning by Hastie et al and Max Kuhn's Applied Predictive modelling cover a lot of the classical techniques.

For univariate time series forecasting "Forecasting Principles and Practice" is great.

For natural language processing foundations Jurafsky's Speech and Language Processing is broadly recommended; for cutting edge natural language processing Stanford's CS224n is great: http://web.stanford.edu/class/cs224n/

[Breza]

I can't suggest Introduction to Statistical Learning enough, it's a fantastic book! I loaned my copy to another data scientist because I didn't want to hog such a valuable resource.