- Event
- Scientific training
Software Carpentry Workshop October 2017
Our goal is to help scientists become more productive by teaching them basic computing skills like program design, version control, testing and task automation.
Start date:
10 October 2017
End date:
11 October 2017
Time:
10h00 - 17h30
Venue:
Earlham Institute
Organiser:
Enquiries:
Registration deadline:
05 October 2017
Cost:
£40.00
About the event.
Important information
Please note, you will be required to bring your own laptop for the purposes of this workshop.
Our goal is to help scientists become more productive by teaching them basic computing skills like program design, version control, testing and task automation. In this two-day bootcamp, short tutorials will alternate with hands-on practical exercises. Participants will be encouraged both to help one another, and to apply what they have learned to their own research problems during and between sessions.
What are the objectives of the course?
You will learn to:
- use the shell to do more in less time
- automate your tasks and pipelines
- write structured programs
- use Git to manage and share information
- how (and how much) to test programs
Target Audience
The course is aimed at researchers in the life science and computational science disciplines at all career stages. We particularly encourage students and post-doctoral scientists to attend, but the course is open to everyone.
Prerequisites
This is aimed at trainees with very little or no prior knowledge of programming.
Organisers and trainers.
Programme.
Day 1 - 10 October 2017
Time
Topic
09:00 - 09:30
Welcome and software set up
09:30 - 10:30
Part 1: Using the shell to do less in more time
10:30 - 11:00
Coffee break
11:00 - 12:30
Part 2: Using the shell to do more in less time
12:30 - 13:30
Lunch
13:30 - 15:30
Using version control to manage and share information
15:30 - 16:00
Coffee break
16:00 - 17:00
Part 1: Python and good programming practice
Day 2 - 11 October 2017
Time
Topic
09:00 - 09:30
Recap and questions
09:30 - 10:30
Part 2: Python and good programming practice
10:30 - 11:00
Coffee break
11:00 - 12:30
Using Python for scientific programming
12:30 - 13:30
Lunch
13:30 - 15:00
Debugging and testing
15:00 - 15:30
Coffee break
15:30 - 16:30
Final exercises
16:30 - 17:00
Final wrap up