Course pages 2017–18

# Scientific Computing Practical Course

**Principal lecturer:** Dr Damon Wischik**Taken by:** Part IA CST 50%, Part IA CST 75%

No. of lectures: 1 (plus an online course with roughly 5 lectures worth of material in the Lent term)

Suggested hours of supervisions: none

Prerequisite courses: Foundations of Computer Science, NST Mathematics

This course is a prerequisite for Foundations of Data Science (Part IB)

## 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