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Timetables

Timetables

Examinations

Exemption Exam Information

Exemption Exams help to determine the proper placement of students into Computer Science courses. Academic credit is not provided for a satisfactory score. All students are required to have prerequisite courses or exemption exams completed before starting any computer science course. Exceptions may apply to mathematics majors with the discrete structures class. The dates listed are for incoming students. If you are a local student, you should consider taking an exemption exam prior to your orientation date. Permission for subsequent courses will only be given once an exam is taken and passed with a satisfactory score.

Students may only take the exemption exam once, and all exams should be taken prior to the start of any semester. Current University students are not eligible for exemption exams if you have already begun the sequence of computer science classes. Regretfully, clarification or additional questions while you are taking the exam cannot be answered. Please answer to the best of your ability. Do not attempt an exam if you do not know all the topics that are covered on the exam, listed below.

Exemption exams are generally graded within 2 weeks, and the results are emailed.

How to schedule:
If you wish to take an exam, please reserve a seat two business days prior to the scheduled exam date by emailing .
In your email, please include

  • your name
  • your UID
  • exam you wish to take

Course handbooks

Course Handbooks



Computer Science

  • 2015 Handbook Supplement for 2nd, 3rd and 4th years, version 1.0
  • 2015 Handbook Supplement for 2nd, 3rd and 4th years, version 2.0
  • 2015 Undergraduate Handbook
  • Referencing Guide

MSc in Computer Science

  • MSc Course Handbook 2015-16

Alphabetical list of courses

A

Advanced Security
Algorithms and Data Structures
Automata, Logic and Games

C

Categorical Quantum Mechanics
Categories, Proofs and Processes
Compilers
Computational Algebraic Topology
Computational Complexity
Computational Learning Theory
Computational Linguistics
Computer Animation
Computer Architecture
Computer Graphics
Computer Networks
Computer Security
Computer-Aided Formal Verification
Computers in Society
Concurrency
Concurrent Algorithms and Data Structures
Concurrent Programming
Continuous Mathematics

D

Database Systems Implementation
Databases
Design and Analysis of Algorithms
Digital Systems
Discrete Mathematics

F

Foundations of Computer Science
Functional Programming

G

Geometric Modelling
Group Design Practical

I

Imperative Programming I
Imperative Programming II
Intelligent Systems
Introduction to Formal Proof

K

Knowledge Representation & Reasoning

L

Lambda Calculus and Types
Linear Algebra
Logic and Proof

M

Machine Learning
Models of Computation

O

Object Oriented Programming

P

Principles of Programming Languages
Probabilistic Model Checking
Probability and Computing
Program Analysis

Q

Quantum Computer Science

R

Requirements

T

Theory of Data and Knowledge Bases

V

Visual Analytics
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