CSI 4103 / 5138: Great Algorithms

University of Ottawa, Fall 2025

Recent Announcements

Teaching Staff

name email office office hour
Andrej Bogdanov
instructor
abogdano@uottawa.ca SITE 5068 Mo 3–5
Yanbo Chen
corrector
ychen918@uottawa.ca SITE 4035

Course Description

Great algorithms are like great works of art. Some are instant hits. Others are challenging at first but grow on you with time. What they have in common is that they change the way we view the world.

Behind every computing advance of the last century stands a great algorithm: error-correction for reliable communication, spectral decomposition and the Fourier transform for data analysis, public-key encryption for e-commerce, gradient descent and backpropagation for machine learning. The aim of the course is to provide a broad perspective on what makes these algorithms tick and the variety of contexts in which they apply.

Schedule

week topic
1 Sep 3 Gaussian elimination
2 Sep 10 Gradient descent
3 Sep 17 Spectral decomposition
4 Sep 24 Fourier transform
5 Oct 1 Backpropagation
6 Oct 8 Secure multiparty computation
Oct 15 Reading Week
Oct 22 Midterm Exam
7 Oct 29 Error correction
8 Nov 5 Public-key encryption
9 Nov 12 Markov Chain Monte Carlo
10 Nov 19 Belief propagation
Nov 26 Project presentations

Homeworks

The assignments are on the scale of a small project. Make sure you have 10-15 hours available to spend on each. The midterm will be in class on 22 October from 8.30 to 9.50.

You are encouraged to collaborate on the homeworks as long as you write your own solutions and acknowledge your collaborators. I discourage you from looking up solutions to homework problems online, unless you have exhausted all other resources.

If you do so, you must provide proper credit and make sure you understand the solution before you write it. You may be asked to present your solution at any time. If you are unable to provide satisfactory explanations you will be considered in breach of academic integrity guidelines and subject to appropriate sanctions.

I discourage uncritical use of chatbots. Their output is not reliable. If you do use them to assist your research, you must acknowledge and properly reference their use. You are solely responsible for any resulting mistakes.

Late submissions won't be accepted.

You can upload your solutons here or bring them to class. Online submissions must be formatted properly and of maximum size 10MB. Do not submit photos. The file name should be your student ID.

Course Information

References

Notes will be provided for every lecture. Here are some additional references.