Course materials for the HU course Data Science Fundamentals
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Data Science Fundamentals

Table of contents



For every week there is a Jupyter Notebook containing examples relating to the subjects of that week


These are optional exercises you can make during the lesson to test your knowledge. You don't need to submit these with the final assignment.


These are PDF versions of the slides i use during classes.

Resources and tips

Feel free to fork this file and add more resources!


Git and the terminal


  • Google and Stack Overflow are your friends. It’s not a shame to Google even really basic concepts. I have been programming for more than twenty years and i still Google really basic stuff every single day.
  • Your code should be properly commented (use #). Good commenting means you explain why you do something, not what you’re doing.
  • Keep your code DRY: Do not Repeat Yourself. If you copy-paste code, you probably could use a function instead.
  • Keep it tidy! Python is a language where indentation matters. This means that if you don’t format your code properly it won’t work.
  • Make sure you all your code is correctly spelled. Python is very picky! If you write If instead of if (note the capital) your code won’t work.
  • If you don’t understand why something isn’t working, try to make an example that is as simple as possible to pinpoint the cause.
  • Pay close attention to the error output you get when you run a command. Google it if you don’t understand it.
  • Note that Python is case sensitive and most file systems are too. When you create a new file only use lowercase characters, no spaces (use the underscore _ instead).
  • Read all the comments in the examples i provide. 90% of the things asked in the assignments are already solved for you there.