Courses
Showing 73 courses.
FOUNDATIONS OF COMPUTER SCIENCE
This introductory computer science course covers core concepts such as logic, proofs, number systems, and probability theory, linking theory to practical applications. It highlights various Computer Science streams and their real-world uses, preparing students for second-year courses and guiding their future academic and career paths.
COMPUTER SCIENCE FUNDAMENTALS I
The nature of Computer Science as a discipline; the design and analysis of algorithms and their implementation as modular, reliable, well-documented programs written in a modern programming language. Intended for students with significant programming experience in at least one high-level block-structured or object-oriented language.
COMPUTER SCIENCE FUNDAMENTALS I
The nature of Computer Science as a discipline; the design and analysis of algorithms and their implementation as modular, reliable, well-documented programs written in a modern programming language. Intended for students with little or no background in programming.
COMPUTER SCIENCE FUNDAMENTALS II
A continuation for both Computer Science 1025A/B and Computer Science 1026A/B . Data organization and manipulation; abstract data types and their implementations in a modern programming language; lists, stacks, queues, trees; recursion; file handling and storage.
INFORMATION SYSTEMS AND DESIGN
Techniques used for determining technological needs of businesses; building and managing systems to meet those needs; development roles of individuals and organizations; planning and management of concepts, personnel and processes; related software tools (spreadsheets, databases). Intended primarily for Management and Organizational Studies students.
MULTIMEDIA AND COMMUNICATION I
This course explores the use of different types of media (e.g., text, images, sound, animation) to convey ideas and facilitate interaction. Topics include the design and use of a range of software tools for media creation and editing, covering image, sound, animation and video. This knowledge will be applied to authoring web sites.
COMPUTER SCIENCE FUNDAMENTALS II
A continuation for Engineering Science 1036A/B . Data organization and manipulation; abstract data types and their implementations in the C programming language; lists, stacks, queues, trees; pointers; recursion; file handling and storage. Intended for students in the Faculty of Engineering.
APPROACHABLE APPS: AN INTRODUCTION TO PROGRAMMING USING JAVASCRIPT
Foundations of app development for the web and mobile devices. An introduction to basic programming and scripting concepts, and technologies such as JavaScript, HTML, and CSS, which will be used to create a variety of apps and games. This course is intended for students with no prior programming or computing background.
MULTIMEDIA AND COMMUNICATION II
This course continues the exploration of popular media and Internet technologies. Topics include advanced photo editing techniques; website development with HTML, CSS, and JavaScript; making websites more interactive; form validation; Bootstrap websites; and the significance of CMS's and e-commerce platforms.
DATA ANALYTICS: PRINCIPLES AND TOOLS
A comprehensive and interdisciplinary introduction to data analytics using modern computing systems, with equal attention to fundamentals and practical aspects. Topics include sources of data, data formats and transformation, usage of spreadsheets and databases, statistical analysis, pattern recognition, data mining, big data, and methods for data presentation and visualization.
DEALING WITH DATA: ANALYSIS AND VISUALIZATION
Essential skills and computational tools for working with data from a number of disciplines. Uses MATLAB for data analysis and visualization through basic statistics, numerical computing, and programming, with interdisciplinary applications ranging from image processing to financial computing, and more. Suitable for both Computer Science and non-Computer Science students.
MODERN SURVIVAL SKILLS I: CODING ESSENTIALS
Essential information processing and coding skills for students. Includes core concepts of algorithms and data structures; creating programs and scripts to address problems that arise in applied research; examples of data sets and analyses drawn from a variety of disciplines. No previous programming background assumed.
MODERN SURVIVAL SKILLS II: PROBLEM SOLVING THROUGH PROGRAMMING
An overview of core data structures and algorithms in computing, with a focus on applications to informatics and analytics in a variety of disciplines. Includes lists, stacks, queues, trees, graphs, and their associated algorithms; sorting, searching, and hashing techniques. Restricted to non-Computer Science students.
INTRODUCTION TO COMPUTER ORGANIZATION AND ARCHITECTURE
This course gives an understanding of what a modern computer can do. It covers the internal representation of various data types and focuses on the architectural components of computers (how these components are interconnected and the nature of the information flow between them). Assembly language is used to reinforce these issues.
APPLIED LOGIC FOR COMPUTER SCIENCE
Propositional and predicate logic; representing static and dynamic properties of real-world systems; logic as a tool for representation, reasoning and calculation; logic and programming.
DATA STRUCTURES AND ALGORITHMS
Lists, stacks, queues, priority queues, trees, graphs, and their associated algorithms; file structures; sorting, searching, and hashing techniques; time and space complexity.
SOFTWARE TOOLS AND SYSTEMS PROGRAMMING
An introduction to software tools and systems programming. Topics include: understanding how programs execute (compilation, linking and loading); an introduction to a complex operating system (UNIX); scripting languages; the C programming language; system calls; memory management; libraries; multi-component program organization and builds; version control; debuggers and profilers.
/Y INTRODUCTION TO SOFTWARE ENGINEERING
A team project course that provides practical experience in the software engineering field. Introduction to the structure and unique characteristics of large software systems, and concepts and techniques in the design, management and implementation of large software systems.
DISCRETE STRUCTURES FOR COMPUTING
This course presents an introduction to the mathematical foundations of computer science, with an emphasis on mathematical reasoning, combinatorial analysis, discrete structures, applications and modeling, and algorithmic thinking. Topics include sets, functions, relations, algorithms, number theory, matrices, mathematical reasoning, counting, graphs and trees.
DATABASES FOR INFORMATICS AND ANALYTICS
A study of relational databases. Theoretical concepts will be covered, including relational algebra and relational calculus. Commercially available database systems will be used to demonstrate concepts such as Structured-Query-Language (SQL), writing code to connect and query a database, query optimization, Atomicity-Consistency-Isolation-Durability (ACID) concepts, and database design.
ARTIFICIAL INTELLIGENCE FOR INFORMATICS AND ANALYTICS
An introduction to artificial intelligence, focused on its application to informatics and analytics. Topics include knowledge representation; logic and reasoning; searching; inferencing; expert systems. Suitable for non Computer Science students.
OPERATING SYSTEMS
Survey of major operating systems; interprocess communication; multi-tasking; scheduling; memory management; performance and measurement issues; trade-offs in operating system design; concurrency and deadlock.
/Y OBJECT-ORIENTED DESIGN AND ANALYSIS
Software design and analysis techniques with particular emphasis on object-oriented design and analysis; a team project will be developed using an object-oriented language such as Java, C++ or Smalltalk.
DATABASES I
A study of relational databases. Theoretical concepts will be covered, including relational algebra and relational calculus. Commercially available database systems will be used to demonstrate concepts such as Structured-Query-Language (SQL), writing code to connect and query a database, query optimization, Atomicity-Consistency-Isolation-Durability (ACID) concepts, and database design.
THEORY OF COMPUTING
Languages as sets of strings over an alphabet; operations on languages; finite automata, regular expressions; language hierarchy; Turing machines; models of computation.
SELECTED TOPICS
Special topics on the frontiers of Computer Science. The topic may vary each year.
/Y SELECTED TOPICS
Special topics on the frontiers of Computer Science. The topic may vary each year.
/Y SELECTED TOPICS
Special topics on the frontiers of Computer Science. The topic may vary each year.
ANALYSIS OF ALGORITHMS I
Upper and lower time and space bounds; levels of intractability; graph algorithms; greedy algorithms; dynamic algorithms; exhaustive search techniques; parallel algorithms.
ORGANIZATION OF PROGRAMMING LANGUAGES
Specification and analysis of programming languages; data types and structures; bindings and access structures; run-time behavior of programs; compilation vs. interpretation. Comparative presentation of at least three programming languages addressing the above concepts.
INTRODUCTION TO ARTIFICIAL INTELLIGENCE
Introduction to Artificial Intelligence; logic programming; heuristic search; knowledge representation; expert systems.
COMPUTER ORGANIZATION
Topics include: semiconductor technologies, gates and circuits, buses, semiconductor memories, peripheral interfaces, I/O techniques, A/D conversion, standards, RISC.
COMPUTER NETWORKS I
Common network protocols; inter-networking; gateways; routers; bridges; survey of commercial architectures; standards.
SOFTWARE PROJECT MANAGEMENT
The software development life cycle; resourcing, scheduling and estimating techniques for software project management; project management organizational concerns, including project economic analysis, human resources, proposal development, risk management, software implementation, and technology-strategic alignment.
/Z PROJECT
A supervised study involving a research paper, the design of or development of a software project.
COMPUTER GRAPHICS I
The viewing pipeline; clipping and visibility problems. The graphical kernel system; picture generation and user interfaces.
PARALLEL AND DISTRIBUTED COMPUTING
This course studies the fundamental aspects of parallel and distributed systems, providing an integrated view of the various facets of software development on such systems: hardware architectures, programming languages, computational models, software development tools and design patterns, performance modelling and analysis, experimenting and measuring, application to scientific computing.
DATABASES II
Advanced database topics such as: query optimization and execution; advanced concurrency control and recovery concepts; distributed databases; XML databases; database security and privacy; databases in the cloud; information retrieval.
CRYPTOGRAPHY AND SECURITY
Survey of the principles and practice of cryptography and network security: classical cryptography, public-key cryptography and cryptographic protocols, network and system security.
DATA SCIENCE II
Students will learn to develop and extend data science methods in order to solve new problems. Approaches covered will include convex loss/regularization, graphical models, and neural networks.
UNSTRUCTURED DATA
Management and analysis of unstructured data, with a focus on text data, for example transaction logs, news text, article abstracts, and microblogs. Overview of unstructured image, audio, and video data. Hands-on experience with modern distributed data management and analysis infrastructure.
INTRODUCTION TO VISUAL ANALYTICS
Students will learn how to conceptualize and design systems that integrate data visualization, interactive machine learning, and human-data interaction to support complex data-driven analytical tasks and activities which humans encounter in different fields. Visual analytics concepts and components will be studied in the context of human-centred computing.
/Y SELECTED TOPICS
Advanced Computer Science topics, reflecting current research interests within the Department. The particular topics will be available from the Department prior to registration.
/Y SELECTED TOPICS
Advanced Computer Science topics, reflecting current research interests within the Department. The particular topics will be available from the Department prior to registration.
/Y SELECTED TOPICS
Advanced Computer Science topics, reflecting current research interests within the Department. The particular topics will be available from the Department prior to registration.
/Y SELECTED TOPICS
Computer Science topics, reflecting current research interests within the Department. The particular topics will be available from the Department prior to registration.
/Y SELECTED TOPICS
Advanced Computer Science topics, reflecting current research interests within the Department. The particular topics will be available from the Department prior to registration.
/Y SELECTED TOPICS
Advanced Computer Science topics, reflecting current research interests within the Department. The particular topics will be available from the Department prior to registration.
ANALYSIS OF ALGORTIHMS II
Parallel, distributed, probabilistic, and geometric algorithms; design and analysis; computational geometry; fractals and graphtals.
INTERNET ALGORITHMICS
This course focuses on the study of algorithms for solving problems that arise from the design and use of large networks, like the Internet. Topics include: Computer networks and internets, distributed algorithms, peer-to-peer systems, the Web graph and searching for information in the Web, caching, and Game Theory.
COMPILER THEORY
Syntax-directed translation; LR(k), LL(k), attribute grammars; code generation; optimization; compiler compilers; code generator generators.
FOUNDATIONS OF MACHINE LEARNING
This course offers a general and comprehensive introduction to fundamental modern topics in machine learning while providing the mathematical basis and conceptual tools needed for understanding machine learning algorithms. It also describes several key aspects of the application of these algorithms.
DEEP LEARNING IN COMPUTER VISION
This course explores Deep Learning and its applications in Computer Vision, focusing on theory and practical skills. Designed for students with basic machine learning knowledge, it empowers them to solve real-world vision-related problems and provides a robust foundation in this rapidly evolving field.
INTRODUCTION TO REINFORCEMENT LEARNING
This course explores fundamental concepts, algorithms, and applications in reinforcement learning, bridging AI and machine learning. Through lectures and practical exercises, students study Markov Decision Processes, Bellman equations, and key algorithms such as Q-learning, and DQN. They discover Reinforcement Learning’s road applicability in robotics, gaming, finance, and healthcare domains.
/Y COMPUTER NETWORKS II
Network layering, performance, management, modelling and simulation; faults and failures.
NETWORK SECURITY
This course will aim at providing a comprehensive understanding of various security issues in an end-to-end network. The list of these topics includes message/user authentication, cryptographic key management, web security, TLS, wireless/5G security, e-mail security, DNS security, IPSec, VPN security, Malware, Firewall, network intrusion detection/prediction/prevention, DoS/DDoS, Cloud and IoT Security.
SELECTED TOPICS ON SCALABLE AND ROBUST DISTRIBUTED SYSTEMS
This course presents fundamental concepts related to the design and implementation of distributed systems. The course teaches the abstractions, design and algorithms that enable the development of scalable and robust distributed systems. Topics include interprocess communication, clocks, replication, data consistency models, consistent hashing, and failure handling.
BIOINFORMATICS THESIS
A project or research paper in an area related to bioinformatics, completed under faculty supervision. An oral presentation plus a written submission will be required.
BIOINFORMATICS TOOLS AND APPLICATIONS
Introduction to popular bioinformatics software tools and their applications in solving complex biological problems; analysis of the algorithms behind bioinformatics tools.
COMPUTATIONAL BIOLOGY
Bioinformatics studies biological problems using biological, computational, and mathematical methods. Computational biology studies computational techniques that can solve biological problems efficiently. This course emphasizes the design, analysis and implementation of algorithms for problems motivated from molecular biology research.
SOFTWARE MAINTENANCE AND CONFIGURATION MANAGMENT
An examination of industrial-style software development issues related to managing and maintaining large-scale software systems; in a group project, students will examine software maintenance and configuration management concepts, tools, techniques, risks and benefits; case studies.
SOFTWARE ARCHITECTURE
Introduction to: advanced system structuring concepts, system qualities, achieving qualities through tactics and architecture patterns, the role of architecturally significant requirements, and documenting and evaluating architectures.
SPECIFICATION TESTING AND QUALITY
Concepts and state of the art techniques in software specification and quality assessment for software engineering; quality attributes; formal specification and analysis; verification and validation.
REQUIREMENTS ENGINEERING
Introduction to system requirements, requirements properties, functionality and quality, requirements engineering processes, including elicitation, analysis, modelling, verification, validation, prioritisation, specification (SRS), change, management, notations, documentation, tools, business context and requirements, and advanced topics.
HUMAN-COMPUTER INTERACTION
Exposure to topics in human-computer interaction, including: frameworks for human-computer interaction; requirements gathering; rapid prototyping; user interface systems and tool kits.
OPEN SOURCE SOFTWARE PROJECT
An examination of large-scale software development in the context of a distributed, multi-university open source software project organized by the Undergraduate Capstone Open Source Projects (UCOSP) initiative (see http://ucosp.ca for details). Students will receive practical hands-on experience in working in software development, as well as valuable soft skills and team experience.
/Y SUMMER OF CODE
An examination of open source software development through Google's annual Summer of Code program. Students are exposed to real-world software development scenarios in mentored projects from a number of open source projects, gaining valuable and practical skills and experience in open source software development and maintenance.
/Y IBM Z XPLORE
The mainframe remains a critical piece of infrastructure for enterprise computing, with experts highly sought after by industry. This course studies mainframe technology through the IBM Z Xplore program. Students are exposed to real-world development through hands-on projects, gaining valuable experience and skills for working with modern mainframe systems.
GAME DEVELOPMENT PROJECT
Industrial-style development issues related to the creation of games of commercial scale and quality, both for entertainment and serious game applications; in a group project, students will examine concepts, theories, tools, technologies, and techniques for code and content generation for modern games.
IMAGE COMPRESSION
Dealing with digital pictures (images) requires far more computer memory and transmission time than is needed for plain text. This course provides students with a solid understanding of the fundamentals and the principles of various digital still-image compression schemes.
GAME PROGRAMMING
Core concepts and techniques of game programming, including the development and usage of game engines for the creation of games. Topics from: game engine architecture; real-time 2D and 3D rendering; character animation; shaders; real-time physics simulation, artificial intelligence, and networking; procedural methods; player input and controls; platform considerations; tools development.
GAME DESIGN
Concepts and issues that arise in the development of games for entertainment and serious game applications, focusing on providing players with more engaging, immersive, and rewarding gameplay experiences. Group project normally required.
THESIS
A project or research paper completed with minimal faculty supervision. An oral presentation plus a written submission will be required.