Oct 3-4, 2018
9:00 am - 4:30 pm
Instructors: Conrad Leonard, Scott Wood
Helpers: Xiaping Lin
Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.
For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".
Who: The course is aimed at graduate students and other researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.
Where: Room 311 ITS training, Education Level 3 Central, 300 Herston Rd Herston QLD. Get directions with OpenStreetMap or Google Maps.
When: Oct 3-4, 2018. Add to your Google Calendar.
Requirements:
Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:
Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.
Contact: Please email conrad.leonard@qimrberghofer.edu.au for more information.
Collaboration: We will be using an interactive etherpad for discussion and examples at http://bionode06.adqimr.ad.lan:9001/p/SWC_2018_Q3
Please be sure to complete these surveys before and after the workshop.
Download the shell-novice-data.zip file and extract it to your /working/[lab_head]/[user] directory on the HPC.
Download the gapminder dataset and extract it to your /working/[lab_head]/[user] directory on the HPC.
Pre-workshop setup | Download files required for the lesson | ||
Day 1 | 09:00 | 1. Introducing the Shell | What is a command shell and why would I use one? |
09:05 | 2. Navigating Files and Directories |
How can I move around on my computer?
How can I see what files and directories I have? How can I specify the location of a file or directory on my computer? |
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09:45 | 3. Working With Files and Directories |
How can I create, copy, and delete files and directories?
How can I edit files? |
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10:15 | 4. Pipes and Filters | How can I combine existing commands to do new things? | |
10:45 | 5. Morning Coffee | Break | |
11:00 | 6. Loops | How can I perform the same actions on many different files? | |
11:30 | 7. Shell Scripts | How can I save and re-use commands? | |
12:00 | 8. Finding Things |
How can I find files?
How can I find things in files? |
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12:30 | Finish | ||
Day 2 | 09:00 | 9. Running and Quitting | How can I run Python programs? |
09:15 | 10. Variables and Assignment | How can I store data in programs? | |
09:35 | 11. Data Types and Type Conversion |
What kinds of data do programs store?
How can I convert one type to another? |
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09:55 | 12. Built-in Functions and Help |
How can I use built-in functions?
How can I find out what they do? What kind of errors can occur in programs? |
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10:20 | 13. Morning Coffee | Break | |
10:35 | 14. Libraries |
How can I use software that other people have written?
How can I find out what that software does? |
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10:55 | 15. Reading Tabular Data into DataFrames | How can I read tabular data? | |
11:15 | 16. Pandas DataFrames | How can I do statistical analysis of tabular data? | |
11:45 | 17. Plotting | How can I plot my data? | |
12:15 | 18. Lunch | Break | |
13:00 | 19. Lists | How can I store multiple values? | |
13:20 | 20. For Loops | How can I make a program do many things? | |
13:45 | 21. Looping Over Data Sets | How can I process many data sets with a single command? | |
14:00 | 22. Writing Functions | How can I create my own functions? | |
14:25 | 23. Variable Scope |
How do function calls actually work?
How can I determine where errors occurred? |
|
14:45 | 24. Afternoon Coffee | Break | |
15:00 | 25. Conditionals | How can programs do different things for different data? | |
15:25 | 26. Programming Style |
How can I make my programs more readable?
How do most programmers format their code? How can programs check their own operation? |
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15:55 | 27. Wrap-Up |
What have we learned?
What else is out there and where do I find it? |
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16:15 | 28. Feedback | How did the class go? | |
16:30 | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.