May 23-24, 2019
9:30 am - 4:30 pm
Instructors: Damien Irving
Helpers: Martin Schweitzer, Bianca Gibson, David Michael Smith
Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Its lessons are domain specific, building on learners' existing knowledge to enable them to quickly apply skills learned to their own research. 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 "Good Enough Practices for Scientific Computing".
Who: The course is for Water Program staff at the Bureau of Meteorology. Participants must have some prior experience using Python. They don't need to be highly proficient, but a familiarity with Python syntax and basic constructs such as loops, lists and conditionals (i.e. if statements) is required.
Where: 11-West Meeting Room, 700 Collins St, Docklands, Melbourne. Get directions with OpenStreetMap or Google Maps.
When: May 23-24, 2019. Add to your Google Calendar.
Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.). They also require access to the Virtual Machines (VMs) that Water Program staff will be working on in future (see below for details).
Code of Conduct: Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.
Contact: Please email Wendy.Sharples@bom.gov.au for more information.
Please be sure to complete these surveys before and after the workshop.
09:30-10:30 | Unix Shell basics |
10:30-11:00 | Morning break |
11:00-12:30 | Automating Tasks with the Unix Shell |
12:30-01:30 | Lunch break |
01:30-03:00 | Introduction to PyAOS libraries and conda |
03:00-03:30 | Afternoon break |
03:30-04:30 | Python data science basics |
10:30-12:30 | Python functions and command line programs |
12:30-01:30 | Lunch break |
01:30-03:00 | Version control with Git and GitLab |
03:00-03:30 | Afternoon break |
03:30-04:30 | Defensive programming and data provenance |
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
Complete lessons notes can be found at the following links:
Python for Atmosphere and Ocean Scientists