Learning to learn

To learn about your scientific field you typically look to:

  • research papers
  • conferences that you attend
  • supervisors
  • courses provided by your institute
  • colleagues

You cannot rely on these sources to learn about effective data analysis!

Many of the most powerful tools for data analysis didn’t - or barely - existed 5 years ago. To know that they exist you need to be regularly watching for new developments. You need to lead your own learning about these developments.

Key sources

  • Twitter
    • More or less everything of use can be found in twitter
    • But you have to find it amid the rubbish!
    • You need to actively search for people who post on the topics you’re interested in
    • I’ve included links to people who post useful stuff
  • YouTube
    • Great for introductory tutorials (e.g. search for bash scripts for beginners)
    • Great for conference presentations (e.g. search for scipy 2020)
  • Discourse/discord servers
    • Increasingly important forums e.g. Dask discourse or Pangeo
    • Sometimes forums are private so won’t turn up in search results
  • Newletters such as the NotANumber newsletter on high performance python
    • Some are very high quality
    • Hard to find
  • Books
    • Wide-ranging and in-depth
    • Can be expensive
    • Go out of date in a few years
  • Online courses
    • Huge number of courses available
    • Hard to find the right one
    • Lots of good free courses e.g. FastAI for machine learning

What about Stack Overflow?

  • Great resource for ideas
  • Provides immediate workarounds
  • Generally does not help you understand fundamental issues


What do you think are the most effective ways to learn about data analysis?

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