BSc Computer Science

4 years

A rigorous four-year program covering the mathematical foundations and engineering practice of computing. Students develop deep expertise in algorithms, systems, and software, with stream options in Artificial Intelligence & Machine Learning, Distributed Systems, Cybersecurity, and Human-Computer Interaction. Graduates are prepared for careers in software engineering, research, and technology leadership, or for graduate study at top institutions worldwide.

Program Highlights

Major, Minor, and Honours options
Streams: AI/ML, Distributed Systems, Cybersecurity, HCI
Joint stream with Engineering for CEAB-accredited Software Engineering
Access to AI & ML Lab, Cybersecurity Lab, and HCI Lab
Co-op option available (16-month extended program)

Course Listing

Code	Course Name	Cr.	Year	Prerequisites	Description
CS 101	Introduction to Computer Science	3	Y1	None	Computational thinking and programming using Python. Algorithms, data structures, problem decomposition, and software development practices.
CS 201	Data Structures	3	Y2	CS 101	Abstract data types, linked lists, trees, heaps, hash tables, graphs, and their algorithmic applications.
CS 210	Computer Organization & Architecture	3	Y2	CS 101	Digital logic, assembly language, memory hierarchy, I/O, pipelining, and processor design.
CS 220	Discrete Mathematics for CS	3	Y2	MATH 101	Logic, proof techniques, sets, functions, combinatorics, graph theory, and number theory.
CS 301	Algorithms & Data Structures	3	Y3	CS 201, MATH 201	Algorithm design paradigms: divide & conquer, dynamic programming, greedy. Complexity theory, P vs NP, graph algorithms, network flow.
CS 310	Operating Systems	3	Y3	CS 210	Processes, threads, scheduling, memory management, file systems, concurrency, and security.
CS 320	Software Engineering	3	Y3	CS 201	Requirements, design patterns, agile methods, testing, version control, and project management.
CS 330	Introduction to Artificial Intelligence	3	Y3	CS 301, MATH 202	Search, constraint satisfaction, logic, planning, probabilistic reasoning, and machine learning basics.
CS 401	Machine Learning	3	Y4	CS 330, STAT 201	Supervised and unsupervised learning, neural networks, deep learning, evaluation, and ethical considerations.
CS 410	Distributed Systems	3	Y4	CS 310	Distributed architectures, consistency, consensus (Raft, Paxos), fault tolerance, replication, and cloud computing.
CS 420	Cybersecurity	3	Y4	CS 310	Threat models, cryptography, network security, web security, secure coding, penetration testing, and privacy.
CS 490	Senior Research Project	6	Y4	Department approval	Two-term supervised research or software project. Culminates in a written report and public presentation.

Assessment

Component	Weight	Notes
Weekly assignments (CS 101)	20%	Due Fridays at 11:59 PM
Lab participation (CS 101)	10%	Attendance + in-lab exercises
Midterm exam (CS 101)	25%	Week 7, in-class, open notes
Final project (CS 101)	20%	Groups of 2; presentations Week 12
Final exam (CS 101)	25%	Scheduled during exam period

CS 101 Weekly Schedule

Textbook: Guttag, J.V. (2021). Introduction to Computation and Programming Using Python (3rd ed.). MIT Press. ISBN: 978-0262542364

Week	Topic	Reading
1	What is computing? Python basics	Ch. 1–2
2	Variables, expressions, I/O	Ch. 2–3
3	Branching and iteration	Ch. 3
4	Functions and scope	Ch. 4
5	Recursion	Ch. 4–5
6	Strings and I/O	Ch. 6
7	MIDTERM + Exceptions	Ch. 7
8	Lists and mutability	Ch. 5
9	Dictionaries and hashing	Ch. 5
10	OOP: classes and objects	Ch. 8
11	Algorithmic complexity	Ch. 9
12	Searching and sorting	Ch. 10
13	Project presentations	—
14	Review + Course wrap-up	—

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