Computer Laboratory

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