Scientific Computing in Python

About

Programming is the science of instructing computers to perform tasks. It is one of the major breakthroughs in human endeavour, with computer programs among the most complex creations.

This module introduces Python, a programming language that has become the standard in scientific computing. Its applications extend far beyond this field, including finance, medicine, mobile technology, online gaming and the film industry. Python’s appeal continues to grow in academia and industry due to its simplicity, versatility and accessibility. It is free to download, easy to learn and supported by a large ecosystem of add-on modules.

Many advances in medical technology have been enabled by Python. This three-week module applies Python to medical and health contexts while showing transferable uses in areas such as investment banking and quantitative finance.

No prior Python knowledge is required, but an interest in biomedicine or health is essential.

Week one
Jupyter Notebook: familiarisation with the environment
NBextensions
Basic syntax and strings
Data types
Built-in functions
Truth and falsehood
Data structures: lists, tuples, dictionaries, sets
Decision-making and flow control
User-defined functions
Handling arrays with NumPy
Working with the OS module
Probability and statistics: NumPy and SciPy for random number generation; Monte Carlo method

Week two
Graphing libraries: basic and advanced plotting with matplotlib; interactive graphics with Plotly
Introduction to data science using Pandas
Series, DataFrames, and methods for data manipulation
Creating DataFrames, CSV, and Excel spreadsheets from raw data
Data visualisation with the Cufflinks library
Medical statistics in Python
Introduction to objects and classes in Python; object-oriented design
Markdown: typesetting, formatting, and producing well-presented reports in Jupyter Notebooks

Week three
Applications in health and biomedicine:
Simulation of random walks in cancer modelling
SEIR epidemic models and modelling disease transmission
Vascular blood flow modelling using VaMpy
Machine learning and data science applications in health
Analysing biomedical data with Biopython
Transferable applications: working with financial databases using Yahoo! Finance and APIs

Course leader

Dr Riaz Ahmad

Course aim

This module aims to:

- Introduce you to coding with no prior experience required.
- Give you a solid grounding in programming in Python.
- Teach you to write effective programmes to solve a variety of problems and develop confidence in the use of libraries.
- Encourage students interested in medical applications to develop skills in Python for disease modelling, health data science and machine learning

Fee info