Course pages 2017–18

**Subsections**

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Scientific Computing Practical Course

This is a practical course taken by Part IA CST students only. It is taught through one introductory lecture, followed by an online course which is equivalent in content to approximately 5 lectures. Students will normally work though the online component at their own pace. The course will be entirely examined through practical exercises.

*Lecturer: Dr D. Wischik*

*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