Good Enough Computing in Science (GECS)
Mini Course at OIST

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Aim

To provide an overview of core software development practices that support efficient research project management and its reproducibility.

Description

Less time for programming, more time for science (and your other stuff).

Target Audience

This course is for researchers who want to learn how to automate repetitive tasks in data analysis. Some prior programming experience is helpful but not required.

Schedule

Time: 10:00-12:00 (Fridays)
Location: L3B700 (near-ish the GS counter)

Part 1 Part 2
January 16 Terminal March 6 Version Control
23 Project Structure 13 Testing
30 Virtual Environments 27 Automation

Drop-in

After every session there will be a drop-in the following week. You can come with questions or problems regarding the course.

Time: 12:00-13:00 (Wednesdays)
Location: C102 (The Cafe Private Room)
Dates: Jan 21, Jan 28, Feb 4 for the Part 1; Mar 11, Mar 25, and Apr 1 for the Part 2.

Setting Up

If you need help with configuring your computer for the course, a session will be held on January 14 Wednesday at the Cafe Private Room during the lunchtime, 12:00-13:00. See Setting up section.

Registration

REGISTER HERE
For official details, see the Graduate School hosted website on TIDA.

People

  • Igors Dubanevics Y4 @ESBU
  • Pin Ju Chou Y1 @CNEU (rotation)
  • Vitoria Yumi Uetuki Nicoleti Y1 @NCU (rotation)

Manifesto

β€œTeach a course you want to attend.”

adapted from Austin Kleon, Steal Like an Artist

As cheesy as it sounds, we are learning from you (probably more at this point) than you will learn from this course. Stupid question permission is granted. Suggestions, tips, and corrections are welcome!

What this course is NOT?

  • Introduction to a specific programming language (e.g., Python, Bash, etc.)
  • Numerical simulations/modeling course
  • High Performance Computing (HPC) training

Inspiration & Credits

Acknowledgements

Arthur Turrell, Greg Wilson and The Carpentries, Justin Bois, Richard McElreath, and the MulQuaBio collective.

References

β€œGood artists copy, great artists steal.”

β€” Pablo Picasso