Programming in Python
Description: This four-week course focuses on task automation using Python programming. Each two hour session will include brief tutorials interspersed with challenge exercises, and assumes participants are familiar with all material in Introduction to Python (working in Jupyter notebooks, basic syntax including variables and functions, importing data, data types and structures, subsetting data). At the end of this course, you will be able to create fully documented and automated workflows to perform data analysis tasks. Note: this course is still being pilot tested.
These materials are based largely on Software Carpentry's [Programming with Python](http://swcarpentry.github.io/python-novice-inflammation/ materials), Copyright (c) Software Carpentry.
Software requirements for this course can be found on fredhutch.io's Software page.
- Week 1: Review of pre-requisites, repeating actions with loops
- Week 2: Analyzing data from multiple files, conditional statements, creating functions
- Week 3: Errors and exceptions, defensive programming
- Week 4: Debugging, modules/packaging for reproducibility
- Each week's materials are described in the script prefaced with the number of the week.
exercises/includes a file for each week representing both the aggregated in-class exercises as well as additional supplemental exercises for practice
solutions/includes the solutions for all files in
resources.mdincludes useful links mentioned during lessons; additional information about continued learning in R as well as Hutch-specific resources can be found on the Data Science Wiki
hackmdio.txtis an archive of the interactive webpage used during lessons