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  • Go out of date in a few years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

Activity

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

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