Learning AimsΒΆ

(Long term goals of training.)

The workshops will, in the long term, enable students to:

  • Be capable of doing their own data analysis.
  • Be future proofed against new software. Students will be able to pick up new version of existing software, or new software, and apply them to their data.
  • Know how to assess computational performance and design appropriate computational controls, and use these to evaluate parameter and software choices.
  • Record their analysis workflow, publish reproducible analyses, and track data provenance manually.
  • Use the appropriate statistical models and tools.
  • Gain in efficiency and expertise on their own, through reading, or via informal interactions in person and online.
  • Choose and apply the appropriate computational resources.
  • Appropriately manage raw data and associated metadata.
  • Identify, troubleshoot, and solve common technical problems on their own, or via informal interactions in person, and/or online.

(Thanks to Tracy Teal for comments on this.)

Also see:

https://twitter.com/JasonWilliamsNY/status/544853305017765888 (Jason Williams)

https://twitter.com/Vaguery/status/544847281124835328 (Bill Tozier)


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