COMP 6901 -- Applied Algorithms, Winter 2022

Announcements | Course information | Assignments and tests | Lecture notes


Course information

The course information below is very tentative! The way the lectures/tests are done and the marking scheme, in particular, are likely to change depending on how long we stay remote and other factors.

Lectures: Until the end of January, synchronous, on Zoom, during scheduled class times (7pm-8:30pm Newfoundland time on Mondays/Wednesdays). The lectures will be recorded and recordings/slides posted on
Brightspace/D2L . If you have trouble accessing Zoom, please let me know as soon as possible and we'll try to find a workaround.
If the situation permits, from February the lectures should revert to in-person: same time in EN-1052.

Instructor: Antonina Kolokolova
Instructor office hours: TBA. Also on Zoom.
Additionally, we will be using discussion boards on Brightspace.

We will be using Brightspace (formerly known as D2L) for submissions, tests, grades, announcements, etc. All the course materials will also be posted here.The Brightspace shell for our course should be available shortly to all registered students; if you cannot register/access Brightspace after the first week of classes, please let me know.

Textbook: There will be no official textbook for this course. We will mostly follow J. Kleinberg, E. Tardos. Algorithm Design, but you do not need to buy it.

Reference books:

We will also use other materials such as research papers.
See the lecture notes from the previous run of this course for more information.

Marking scheme: (tentative!): The course mark is determined by your performance on assignments, drills, drill-writing project, and written exams; there is also an optional oral exam. If we are not able to have written exams in person, the marking scheme will be changed; in that case, already submitted work may be reweighted.

Description: The goal of this course is to study both classical and advanced algorithm design techniques with emphasis on real-world applications. We will cover greedy algorithms, dynamic programming, backtracking, network flows as well more advanced topics. Time permitting, we will consider randomized, parallel and distributed algorithms, and/or streaming algorithms.

Prerequisites: This course assumes proficiency in the core subjects of computer science: programming, discrete math, and basic data structures/algorithms. In particular, I will assume that you can read and write proofs, know basic probability theory and combinatorics, know basic data structures and algorithm complexity analysis, can read and write pseudocode, and can program fluently in some programming language such as Python. Check our undergraduate courses COMP 1001, COMP 1002 and COMP 2002, and make sure you are comfortable with the material covered there; this should take care of most of the skills you need to succeed in COMP 6901.


Policy on collaboration and plagiarism.
The main rule is: the work you submit must be your own. You are encouraged to work together on problems and ask questions about them on the discussion forum; however, you must work out all answers you submit on drills, exams, etc by yourself, without looking things up online or interacting with anybody except for the instructor. You are welcome to work together on the assignments, but write solutions by yourself. If you come across an answer to a similar problem while researching a topic, you must reference the source and restate the solution in your own words, then you can receive full marks.
Plagiarism is a serious academic offence and will be dealt with accordingly. Posting any course content (assignments, drills, exams, practice problems) on the internet, with or without solutions, or using services such as Chegg is a serious academic misconduct which will be reported.