Department of Computer Science and Technology

Course pages 2019–20

Scientific Computing Practical Course

Lecture notes


Getting started

All you need is to start a Jupyter notebook, and get coding. It's up to you where to run your notebook — some suggestions are

You don't have to follow any template — you can just create your own notebook from scratch and start working. However, there is a simple template available in the notebook library. The template notebook also gives details of how to submit your answers: in brief,

# If the autograder isn't installed, you need to install it:
!pip3 install ucamcl

import ucamcl
GRADER = ucamcl.autograder('', course='scicomp').subsection('tick2a')

q = GRADER.fetch_question('q1')
ans = ...
GRADER.submit_answer(q, ans)

Resources elsewhere

  • The notebook library also has a tips for data import and cleanup, and will have several of example data analyses
  • Moodle: timetable, ticking arrangements, help forum