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C1 Research Computing and Software Development

Boris Bolliet and Alessandro Favero · University of Cambridge · MPhil in Data Intensive Science · Michaelmas 2026

Aims

The course develops the computing and software-development skills required of a researcher and data scientist in the age of AI: the ability to create, review, correct, distribute and take ownership of scientific code.

Schedule

Dates and topics are listed in the lecture overview.

Four example classes, in fifteen groups, complement the lectures; dates, rooms and demonstrators are listed under Example Classes.

Lecture format

Fifty minutes, from five past to five to the hour: slides interleaved with live demonstrations at the terminal. The commands of each demonstration, with their expected output, are in the Terminal boxes of the notes.

Slides and notes are released before each lecture; lecture recordings and transcripts after it.

Practical work

Every command in the notes is intended to be run in a terminal. Predicting the output before running a command, and reading an error message in full before changing anything, are recommended practice.

Course assistant

A chat assistant (bottom right of every page) answers questions from the lecture notes, with a citation to the page used. Access is restricted to students of the course: the username is the CRSid and the password is the one given in the lectures.

Assessment

  • Coursework: released mid-November · due mid-December
  • Examination: January 2027 (date and venue to be confirmed)
  • Past papers: the examinations and coursework of the last three years, questions only, under Past papers (course login, MPhil in Data Intensive Science and Computational Biology)
  • Last year's material: the public material of the 2025–26 course is at researchcomputing.readthedocs.io

Scope

The course is shared between the MPhil in Data Intensive Science and four other programmes: the MPhil in Economics and Data Science, Astrophysics, Planetary Science and Life in the Universe, and Computational Biology. Information about assessments and coursework given here and in class applies to the MPhil in Data Intensive Science only; the coursework brief and marking scheme are on Moodle. Assessment for students of the MPhil in Economics and Data Science is arranged separately by the Faculty of Economics; enquiries should be addressed to the director of that programme, Alexei Onatski.