Summary of co​urse content

Python is one of the most widely used and growing programming languages. The course will introduce the students to the different concepts in Python programming, such as loops, conditional statements, development of functions, construction of bioinformatical pipelines and plotting. Biomedical data scientists can use Python for data analysis and to implement their own functions, which can be grouped into packages and shared with other purveyors. This is a customized programming course tailored for the training backgrounds of biologists.

This is a Technology-Enhanced Learning (TEL) course (100%).

Aims and objectives

The aim of this module is to allow students to gain proficiency in Python, with particular focus on data analysis and visualization.

Syllabus

Week 1	Basic program structure - Using Google Colab to write Python scripts
Week 2	Boolean data types, relational operators, selection - Using variables and conditional statements
Week 3	Repetition and loops - for loops
Week 4	Repetition and loops - while loops, pass, continue, break statements
Week 5	Abstraction, strings, composites - Strings and lists
Week 6	Abstraction, strings, composites - Dictionaries
Week 7	Function development - Using and constructing functions
Week 8	Sets - Using sets and set theory
Week 9	Plotting in matplotlib - Introduction to plotting with matplotlib and seaborn
Week 10	Statistical packages in Python - Introduction to numpy and scipy, Project
Week 11	Building pipelines in python - Using O​S module to run external software, Project
Week 12	Gene function prediction I: Introduction - Project
Week 13	Gene function prediction II: Network analysis - Project

Assessment

Participation and MCQs	Individual	20%
MCQ Quizzes	Individual	30%
Hands-on Exercises	Individual	20%
Project	Group	30%
		100%