Department of Computer Science and Technology

Course pages 2017–18


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)


This course is a hands-on introduction to using computers to investigate scientific models and data.


  • 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.


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