Randomness and Computation

Spring 2020

Alice in Randomland
One of the most remarkable developments in Computer Science over the past 30 years has been the realization that the ability of computers to toss coins can lead to algorithms that are more efficient, conceptually simpler and more elegant that their best known deterministic counterparts. Randomization has by now become a ubiquitous tool in computation.

This course will survey several of the most widely used techniques in this context, illustrating them with examples taken from algorithms, random structures and combinatorics. Our goal is to provide a solid background in the key ideas used in the design and analysis of randomized algorithms and probabilistic processes.

Students taking this course should have already completed a good Algorithms courses (with theoretical underpinnings), and have excellent Maths.

Course Information


We planned to have 5 tutorials during the semester, on weeks 4, 6, 7, 8 and 10.
However week 8 was cancelled due to the strike, and week 10 will move into week 11 (Thurs 2nd and Fri 3rd April) and online because of the Coronavirus shutdown.

We had two options, and students could attend whichever they preferred:

Tutorial Sheets will be available on Learn.


Lecture recording will appear in Learn.

Slides below the gray line are from the last year. They will be updated as we progress.


There will be two courseworks in total: the first will be marked and (formative) feedback returned, but will not contribute to the final mark. They will be available on Learn.

Course Outline

Here is a rough outline of the course material:


Please read the following guidelines regarding coursework: