Scientific Computing
Principal lecturer: Dr Damon Wischik
Additional lecturer: Prof Andrew Moore
Taken by: Part IA CST
Term: Michaelmas (continuing in Lent)
Hours: 1
Format: In-person lectures
Suggested hours of supervisions: 1
Moodle, timetable
Aims
This course is a hands-on introduction to using computers to investigate scientific models and data.
Syllabus
- Python notebooks. Overview of the Python programming language. Use of notebooks for scientific computing.
- Numerical computation. Writing fast vectorized code in numpy. Optimization and fitting. Simulation.
- Working with data. Data import. Common ways to summarize and plot data, for univariate and multivariate analysis.
Objectives
At the end of the course students should
- be able to import data, plot it, and summarize it appropriately
- be able to write fast vectorized code for scientific / data work