I don't think there's a definite one-size-fits-all answer to that, it will depend on what's most enjoyable to you, what jobs you'll be applying to etc. My perso

I don't think there's a definite one-size-fits-all answer to that, it will depend on what's most enjoyable to you, what jobs you'll be applying to etc. My personal recommendation (which is based on my n=1 subjective experience) is: - python DS ecosystem; fundamentals: numpy pandas matplotlib seaborn sklearn scipy. From there you can branch in many different directions - interactive visualization libraries (e.g. plotly / bokeh), stats / probability stuff (statsmodels / pymc3), NLP, sklearn addons, ML explainability, ... - solid "software engineering" - writing good code, unit tests, documentation, logging, basics of deploying a service - TF / pytorch if you want to get into the deep learning hype Best of luck, and more importantly, enjoy!