Course Description

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs and customize more complex code to fit their needs.

Course Objectives

After this course you should be able to:

• Edit and run Python code
• Write file-processing python programs that produce output to the terminal and/or external files
• Create stand-alone python programs to process biological data
• Know how to develop your skills in Python after the course

Topics Covered

Week 1

• Introduction
• Data types

Week 2

• Conditional execution
• Loops

Week 3

• Files
• Delimited files

Week 4

• Case studies
• Practice

Course Materials

Week 1

• Introduction
• Simple data types
• Lists and Dictionaries

Week 2

• Conditional execution
• Loops

Week 3

• Recap
• Files

Week 4

• Use Cases/Practice

Additional Reading

• Additional Reading
• Pandas Reading from a CSV
• Pandas Selecting data

Course Presenters

• Maria Doyle, Research Computing Facility
• Richard Lupat, Bioinformatics Core
• Miriam Yeung, Dawson Labs

Course Helpers

(includes all above)

• Lara Petelin, Parkville Familial Cancer Centre

Acknowledgements

This course is run by the Peter Mac Data Science Training team and is based on the Python course run by the University of Cambridge

Useful Resources

• The Python Software Foundation