non thesis masters computer science in canada

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Master of Science (M.Sc.) in Computer Science

[Note: The M.Sc. programs have undergone a revision starting Fall 2020. The main change is a reduction in the course credit requirements and an increase in the research credit requirements. Students who began the M.Sc. program prior to Fall 2020 may follow the requirements of the new program if they wish.]

We offer two M.Sc. programs - the Thesis and Non-Thesis. The Non-Thesis program will be sometimes referred to as the Project option since it substitutes a project (and additional courses) for a thesis. Both programs are designed to take between 1.5 and 2 years. The maximum allowable is 3 years. Students begin in the Thesis program, and may switch to the Project option any time after their second semester.

Students intending to pursue a Ph.D. after the M.Sc. should follow the Thesis program rather than the Non-Thesis program. Alternatively, students may apply to be fast-tracked to the Ph.D. program without completing the M.Sc.. Such applicants must have completed a minimum of two and a maximum of four full-time semesters, according to GPS rules. For more information, see the bottom of this web page.

Students in either M.Sc. program have a minimum residence requirement of three full-time semesters. Students may register for the Summer semester if they wish to complete their residence requirements. For further details on student status, see here .

Students should take a minimum of two Complementary courses in their first semester and should complete all four Complementary courses by the end of their second semester. In addition, students in their first two semesters should take the Seminar courses COMP 602 (Fall) and 603 (Winter).

Here is a brief summary of the requirements of the two M.Sc. programs. Both programs require:

• three full-time terms of residence
• two seminar courses COMP 602 and 603
• a total of at least 45 credits

In addition, the Thesis program requires:

• at least 14 credits of COMP (or approved) Complementary coursesat the 500 level or higher, which satisfy a Breadth Requirement (see below)
• a thesis with significant scholarly content

and the Non-Thesis program requires:

• at least 28 credits of COMP (or approved) Complementary courses at the 500 level or higher, which satisfy a Breadth Requirement (see below);
• a research project (see guidelines )

Further details on the two programs including the course Breadth Requirement, the Letter of Understanding agreement between student and supervisor, and the Progress Report are given below.

M.Sc. Computer Science (Thesis) (45 credits)

Thesis courses (29 credits).

At least 29 credits selected from:

• COMP 691 Thesis Research 1 (3 credits)
• COMP 696 Thesis Research 2 (3 credits)
• COMP 697 Thesis Research 3 (4 credits)
• COMP 698 Thesis Research 4 (10 credits)
• COMP 699 Thesis Research 5 (12 credits)

Required Courses (2 credits)

• COMP 602 Computer Science Seminar 1 (1 credit)
• COMP 603 Computer Science Seminar 2 (1 credit)

Complementary Courses (14 credits)

At least 14 credits of COMP (or approved by MSc Graduate Program Director) courses at the 500-, 600-, or 700-level. Complementary courses must satisfy a Computer Science Breadth Requirement, with at least one course in two of the Theory, Systems, and Application areas.

Course Breadth Requirement

Courses must be taken from at least two of the three categories below (Theory, Systems, and Applications). The category of any course not listed below such as a new course or a 500 level Topics courses follows the general pattern of the existing courses. In cases of doubt, students should contact the Computer Science Graduate (M.Sc.) Program Director.

Category A: Theory

COMP 523 Language-based Security (3 credits) COMP 524 Theoretical Foundations of Programming Languages (3 credits) COMP 525 Formal Verification (3 credits) COMP 527 Logic and Computation COMP 531 Advanced Theory of Computation (3 credits) COMP 540 Matrix Computations (4 credits) COMP 547 Cryptography and Data Security (4 credits) COMP 552 Combinatorial Optimization (4 credits) COMP 553 Algorithmic Game Theory (4 credits) COMP 554 Approximation Algorithms (4 credits) COMP 560 Graph Algorithms and Applications (3 credits) COMP 566 Discrete Optimization 1 (3 credits) COMP 567 Discrete Optimization 2 (3 credits) COMP 610 Information Structures 1 (4 credits) COMP 627 Theoretical Programming Languages (4 credits) COMP 642 Numerical Estimation Methods (4 credits) COMP 647 Advanced Cryptography (4 credits) COMP 649 Quantum Cryptography (4 credits) COMP 690 Probabilistic Analysis of Algorithms (4 credits) COMP 760 Advanced Topics Theory 1 (4 credits) COMP 761 Advanced Topics Theory 2 (4 credits)

Category B: Systems

COMP 512 Distributed Systems (4 credits) COMP 520 Compiler Design (4 credits) COMP 529 Software Architecture (4 credits) COMP 533 Model-Driven Software Development (3 credits) COMP 535 Computer Networks 1 (4 credits) COMP 575 Fundamentals of Distributed Algorithms (3 credits) COMP 612 Database Programming Principles (4 credits) COMP 614 Distributed Data Management (4 credits) COMP 621 Program Analysis and Transformations (4 credits) COMP 655 Distributed Simulation (4 credits) COMP 667 Software Fault Tolerance (4 credits) COMP 762 Advanced Topics Programming 1 (4 credits) COMP 763 Advanced Topics Programming 2 (4 credits) COMP 764 Advanced Topics Systems 1 (4 credits) COMP 765 Advanced Topics Systems 2 (4 credits)

Category C: Applications

COMP 521 Modern Computer Games (4 credits) COMP 522 Modellin and Simulation (4 credits) COMP 526 Probabilistic Reasoning and AI (3 credits) COMP 546 Computational Perception (4 credits) COMP 550 Natural Language Processing (3 credits) COMP 551 Applied Machine Learning (4 credits) COMP 557 Fundamentals of Computer Graphics (4 credits) COMP 558 Fundamentals of Computer Vision (4 credits) COMP 559 Fundamentals of Computer Animation (4 credits) COMP 561 Computational Biology Methods and Research (4 credits) COMP 564 Advanced Computational Biology Methods and Research (3 credits) COMP 579 Reinforcement Learning (4 credits) COMP 618 Bioinformatics: Functional Genomics (3 credits) COMP 680 Mining Biological Sequences (4 credits) COMP 652 Machine Learning (4 credits) COMP 766 Advanced Topics Applications 1 (4 credits) COMP 767 Advanced Topics: Applications 2 (4 credits)

M.Sc. Computer Science (Non-Thesis) (45 credits)

Research project courses (15 credits).

• COMP 693 Research Project 1 (3 credits)
• COMP 694 Research Project 2 (6 credits)
• COMP 695 Research Project 3 (6 credits)

Students who have taken any Thesis Research (1-5) courses prior to switching to the Non-Thesis program and who wish to use these credits (instead of Research Project course credits) toward their M.Sc. Non-Thesis program should contact the M.Sc. Graduate Program Director.

Complementary Courses (28 credits)

At least 28 credits of COMP (or approved by MSc Graduate Program Director) courses including at least three 4-credit courses at the 500, 600, or 700 level. The courses must meet the same Breadth Requirement as in the Thesis program (see above), namely courses must be from at least two of the three areas of Theory, Systems, and Applications.

Letter of Understanding

The letter of understanding must be filled by the student and the supervisor(s) at the initial meeting and signed by both. This letter of understanding must be uploaded by the student into MyProgress. If there are significant changes in the understanding, a new letter can be created and uploaded.

Annual Progress Report

Each student must meet annually with his/her supervisor or co-supervisors to assess the progress made during the previous year, and describe plans for the coming year. The progress form below must be filled by the student, discussed with the supervisor, and signed by both. A progress form must be filled each year (except the first year) before September 30th, and submitted to Ann Jack.

Annual Progress Form (PDF document)

Fast-tracking from the M.Sc. Thesis to the Ph.D. program

Excellent M.Sc. students who would like to pursue doctoral studies can apply to be "fast-tracked" to the Ph.D. program, after having completed a minimum of two and maximum of four full time semesters of the MSc Thesis program. Each fast-tracking application will be evaluated by the Ph.D. committee, in concert with the proposed Ph.D. supervisor, on a case-by-case basis. Evaluation criteria will include excellence of the academic record and achievements in research. M.Sc. students interested in fast-tracking to the Ph.D. program should discuss this option with their supervisor.

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Master of Computer Science

• Degree offered: Master of Computer Science (MCS)
• Registration status options: Full-time; Part-time
• Language of instruction: English
• within two years of full-time study
• For immigration purposes, the summer term (May to August) for this master’s program with Coursework and Project is considered a regularly scheduled break approved by the University. Students should resume full-time studies in September.
• Academic units: Faculty of Engineering , School of Electrical Engineering and Computer Science , Ottawa-Carleton Institute for Computer Science (OCICS).

Program Description

Ottawa-Carleton Joint Program

Students who wish to pursue studies in computer science leading to the degree of Master of Computer Science (MCS) or Doctor of Philosophy in Computer Science (PhD) can do so in joint programs offered by the School of Electrical Engineering and Computer Science (EECS) at the University of Ottawa and the School of Computer Science at Carleton University under the auspices of the Ottawa-Carleton Institute for Computer Science (OCICS). The Institute is responsible for supervising these programs and for providing a framework for interaction between the universities in graduate computer science education. In addition to the faculty members from the two computer science programs, the Institute also has members with computer science expertise from other departments.

The School of Computer Science is a participating unit in the collaborative program in bioinformatics at the master’s level.

Other Programs Offered Within the Same Discipline or in a Related Area

• Master of Computer Science Specialization in Bioinformatics (MCS)
• Doctorate in Philosophy Computer Science (PhD)

Fees and Funding

• Program fees:

The estimated amount for university fees associated with this program are available under the section Finance your studies .

International students enrolled in a French-language program of study may be eligible for a differential tuition fee exemption .

• To learn about possibilities for financing your graduate studies, consult the Awards and financial support section.
• Programs are governed by the general regulations in effect for graduate studies and the regulations in effect at Carleton University.
• In accordance with the University of Ottawa regulation, students have the right to complete their assignments, examinations, research papers, and theses in French or in English. In addition, research activities can be conducted in either English or French or both depending on the language used by the professor and the members of the research group.
• Students may include courses from both universities in their programs, and may select a supervisor from either university, but they should apply to the university with which their supervisor is associated. Their study program is administered by the university at which they are enrolled and is subject to its regulations.

Program Contact Information

Graduate Studies Office, Faculty of Engineering STE 1024 800 King Edward Ave. Ottawa ON Canada K1N 6N5

Tel.: 613-562-5347 Fax.: 613-562-5129 Email: [email protected]

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For the most accurate and up to date information on application deadlines, language tests and other admission requirements, please visit the  specific requirements  webpage.

To be eligible, candidates must:

• Have a bachelor of science degree with honours in computer science (or equivalent), with a minimum average of B (70%).

Note: International candidates must check the admission equivalencies for the diploma they received in their country of origin.

• Identify at least one professor who is willing to supervise your research and thesis. We recommend that you contact potential thesis supervisors as soon as possible.

The Accelerated Stream has three additional requirements. Candidates must:

• Complete up to 6 units from the OCICS master’s courses each with 70% (B) or higher grade (taken during their Bachelor’s program in Computer Science or Software Engineering).
• Have an admission average of A- (80%) or higher.
• Have a thesis supervisor.

Language Requirements

Applicants must be able to understand and fluently speak the language of instruction (French or English) in the program to which they are applying. Proof of linguistic proficiency may be required.

Applicants whose first language is neither French nor English must provide proof of proficiency in the language of instruction.

Note: Candidates are responsible for any fees associated with the language tests.

• The admission requirements listed above are minimum requirements and do not guarantee admission to the program.
• Admissions are governed by the general regulations in effect for graduate studies.

Applying to the Co-op Option

In order to apply to the co-op option, you must first be admitted to a program that offers co-op. The co-op option is not available to MCS students in the Accelerated Stream.

Your application must be submitted by the end of the first month of enrollment in your primary program, i.e., by the end of September.

Admission to the co-op option occurs on a competitive basis and is managed by the Co-op Office . Enquiries should be directed to that office.

To be admitted to the co-op option, you must:  

• Be enrolled as a full-time student in the master’s in computer science;
• Have a cumulative grade point average of 7.0 or 75%;
• Begin the program in the Fall term;
• Be a Canadian citizen, a permanent resident or an international student (authorization or diplomat)
• Pay the required CO-OP fees.

Qualifying Program

Applicants who lack the required undergraduate preparation may be admitted to a qualifying-year program. The basis for admission to the qualifying year of the master’s program will normally be an honours degree in a related discipline with a B average (70%), provided that the honours program in question includes the equivalent of three years of an honours computer science program. A major degree holder with superior academic standing may be considered for admission to the qualifying year with suitable background preparation.

Master’s with Thesis

Students must meet the following requirements:

Course selection must be approved by the student's academic advisor. A maximum of two three-unit courses at the 4000 level are permitted.

Consult the Ottawa-Carleton Institute for Computer Science for a complete list of courses per category

A student may be permitted to carry out thesis work off campus provided suitable arrangements are made for supervision and experimental work, and prior approval is obtained from the Joint Program Committee.

Students are responsible for ensuring they have met all of the thesis requirements .

Master’s with Thesis, Accelerated Stream

Course selection must be approved by the student's academic advisor. For students in the Accelerated Stream, the two OCICS courses taken as part of their undergraduate degree can be used to satisfy at most two of the above category requirements.

Consult the  Ottawa-Carleton Institute for Computer Science for a complete list of courses per category

Master’s with Coursework and Project

Requirements for this program have been modified. Please consult the  2018-2019 calendars  for the previous requirements.

To receive this Master’s degree, a student enrolled in the program must successfully complete 30 course units.

Subject to the approval of the graduate coordinator, a student may take up to half of the course units in the program in other disciplines (e.g. electrical engineering, mathematics and physics).

Co-op Option

(Available to students enrolled in the thesis option or the coursework and project option.)

To complete a master’s with coursework and project, you must meet the following requirements :

• Maintain a cumulative grade point average of 7.0 or 75%;
• Obtain a satisfactory grade (P) for each co-op work term: CGI 6001 , CGI 6002 .
• Each work term is graded P/F (pass/fail), based on the employer’s report and on the written report completed by the student. (The report must be 30 pages long, including appendices.) The report is evaluated by the professor in charge of the graduate co-op option in Computer Science.
• The units awarded for co-op terms may not be used to obtain equivalences for other courses. In other words, the co-op units are additional to the minimum requirements of the degree.

Fast-Track from Master’s to PhD

Students enrolled in the master’s program in computer science at the University of Ottawa may be eligible to fast-track directly into the doctoral program without writing a master’s thesis. For additional information, please consult the “Admission Requirements” section of the PhD program.

Note: Students in the Accelerated Stream of the MCS are not eligible for fast-track to the PhD.

Minimum Requirements

The passing grade in all courses is B.

Research Fields & Facilities

Located in the heart of Canada’s capital, a few steps away from Parliament Hill, the University of Ottawa is among Canada’s top 10 research universities.

uOttawa focuses research strengths and efforts in four Strategic Areas of Development in Research (SADRs):

• Canada and the World
• Molecular and Environmental Sciences

With cutting-edge research, our graduate students, researchers and educators strongly influence national and international priorities.

Research at the Faculty of Engineering

Areas of research:

• Chemical and Biological Engineering
• Civil Engineering
• Electrical Engineering and Computer Science
• Mechanical Engineering

For more information, refer to the list of faculty members and their research fields on Uniweb . 

CSI 5100 Data Integration (3 units)

Materialized and virtual approaches to integration of heterogeneous and independent data sources. Emphasis on data models, architectures, logic-based techniques for query processing, metadata and consistency management, the role of XML and ontologies in data integration; connections to schema mapping, data exchange, and P2P systems. This course is equivalent to COMP 5306 at Carleton University.

Course Component: Lecture

CSI 5101 Knowledge Representation (3 units)

KR is concerned with representing knowledge and using it in computers. Emphasis on logic-based languages for KR, and automated reasoning techniques and systems; important applications of this traditional area of AI to ontologies and semantic web. This course is equivalent to COMP 5307 at Carleton University.

CSI 5102 Topics in Medical Computing (3 units)

Introductory course on data structures, algorithms, techniques, and software development related to medical computing (in particular spatial modeling). Topics may include: computational geometry algorithms for cancer treatment, medical imaging, spatial data compression algorithms, dynamic programming for DNA analysis. This course is equivalent to COMP 5308 at Carleton University.

CSI 5105 Network Security and Cryptography (3 units)

Advanced methodologies selected from symmetric and public key cryptography, network security protocols and infrastructure, identification, anonymity, privacy technologies, secret-sharing, intrusion detection, firewalls, access control technologies, and defending network attacks. This course is equivalent to COMP 5406 at Carleton University.

Prerequisites: familiarity with basic concepts in networks, network security, and applied cryptography.

CSI 5106 Cryptography (3 units)

Security in encryption algorithms. Encryption and decryption. Entropy, equivocation, and unicity distance. Cryptanalysis and computational complexity. Substitution, transposition, and product ciphers. Symmetric ciphers: block and stream modes. Modular arithmetic. Public key cryptosystems. Factorization methods. Elliptic curve, lattice-based, and homomorphic cryptography. Proofs of security.

CSI 5107 Principle of Intelligent Transportation Systems (3 units)

Fundamental Concepts of ITS. Computer Information and Communication for ITS. The Backbone of ITS Communication, Network Topologies and Configurations. ITS Models and Evaluation Methods. Advanced Transportation Management Systems (ATMS). Advanced Traveler Information Systems (ATIS). Advanced Driver Assistant Systems. Data Stream Management System (DSMS) in the intelligent transportation Systems. Intelligent Traffic Control Algorithms. Traffic Demand Modeling and Analysis. Incident Detection and Collusion Avoidance Algorithms. Smart Mobility and GPS Localization Algorithms. Software Defined Network for ITS. Security & Privacy in ITS

CSI 5108 Introduction to Convex Optimization (3 units)

Mathematics of optimization: linear, nonlinear and convex problems. Convex and affine sets. Convex, quasiconvex and log-convex functions. Operations preserving convexity. Recognizing and formulating convex optimization problems. The Lagrange function, optimality conditions, duality, geometric and saddle-point interpretations. Least-norm, regularized and robust approximations. Statistical estimation, detector design. Adaptive antennas. Geometric problems (networks). Algorithms.

CSI 5110 Principles of Formal Software Development (3 units)

Methodologies in formal software specification, development, and verification. The use of theorem proving, automated deduction, and other related formal methods for software correctness. Applications in program verification and secure computation. This course is equivalent to COMP 5707 at Carleton University.

CSI 5111 Software Quality Engineering (3 units)

Software quality issues. Quality components and metrics. Software process quality. Software reliability engineering. Software design for testability. Requirements capture and validation. Systematic design validation; grey-box approach, test design, implementation and management, case studies in validation and verification of communications software. Object-oriented design and test. Theoretical aspects. This course is equivalent to COMP 5501 at Carleton University.

CSI 5112 Software Engineering (3 units)

Topics of current interest in Software Engineering, such as requirements engineering, precise and advanced modelling, development processes, change management, standards, and emerging types of applications. This course is equivalent to COMP 5207 at Carleton University.

CSI 5113 Foundations Programming Languages (3 units)

Advanced study of programming paradigms from a practical perspective. Paradigms may include functional, imperative, concurrent, distributed, generative, aspect- and object-oriented, and logic programming. Emphasis on underlying principles. Topics may include: types, modules, inheritance, semantics, continuations, abstraction and reflection. This course is equivalent to COMP 5001 at Carleton University.

CSI 5115 Database Analysis and Design (3 units)

The dimensional and multidimensional data models for data warehousing. Data dependencies and decomposition. Structure and use of data definition and manipulation languages. Database economics, engineering, deployment and evolution. Issues in integrity, security, the Internet and distributed databases. Relationships to decision support systems. This course is equivalent to COMP 5503 at Carleton University.

Course Component: Discussion Group, Laboratory, Lecture, Research, Seminar, Work Term, Theory and Laboratory, Tutorial

CSI 5116 Authentication and Software Security (3 units)

Specialized topics in security including advanced authentication techniques, user interface aspects, electronic and digital signatures, security infrastructures and protocols, software vulnerabilities affecting security, non-secure software and hosts, protecting software and digital content. This course is equivalent to COMP 5407 at Carleton University.

CSI 5118 Automated Verification and Validation of Software (3 units)

Topics in formal test derivation methods, test management, high-level, CASE-based verification and validation, data-flow & control-flow measures and metrics for assessing quality of designs and code, regression analysis & testing. This course is equivalent to COMP 5302 at Carleton University.

CSI 5121 Advanced Data Structures (3 units)

Simple methods of data structure design and analysis that lead to efficient data structures for several problems. Topics include randomized binary search trees, persistence, fractional cascading, self-adjusting data structures, van Emde Boas trees, tries, randomized heaps, and lowest common ancestor queries. This course is equivalent to COMP 5408 at Carleton University.

CSI 5122 Software Usability (3 units)

Design principles and metrics for usability. Qualitative and quantitative methods for the evaluation of software system usability: Heuristic evaluation, usability testing, usability inspections and walkthroughs, cognitive walkthroughs, formal usability experimentation. Ethical concerns when performing studies with test users. Economics of usability. Integration of usability engineering into the software engineering lifecycle. This course is equivalent to COMP 5301 at Carleton University.

CSI 5124 Computational Aspects of Geographic Information Systems (3 units)

Computational perspective of geographic information systems (GIS). Data representations and their operations on raster and vector devices: e.g., quadtrees, grid files, digital elevation models, triangular irregular network models. Analysis and design of efficient algorithms for solving GIS problems: visibility queries, point location, facility location. This course is equivalent to COMP 5204 at Carleton University.

CSI 5126 Algorithms in Bioinformatics (3 units)

Fundamental mathematical and algorithmic concepts underlying computational molecular biology; physical and genetic mapping, sequence analysis (including alignment and probabilistic models), genomic rearrangement, phylogenetic inference, computational proteomics and systemics modelling of the whole cell. This course is equivalent to COMP 5108 at Carleton University.

CSI 5127 Applied Computational Geometry (3 units)

Design and analysis of efficient algorithms for solving geometric problems in applied fields such as Geometric Network Design, Geometric Routing and Searching. Geometric spanners, Greedy spanners, Theta-Graphs, Yao-Graphs, Well-Separated Pair Decomposition, Delaunay Triangulations. Introduction to the game of Cops and Robbers. This course is equivalent to COMP 5409 at Carleton University.

CSI 5128 Swarm Intelligence (3 units)

Collective computation, collective action, and principles of self-organization in social agent systems. Algorithms for combinatorial optimization problems, division of labour, task allocation, task switching, and task sequencing with applications in security, routing, wireless and ad hoc networks and distributed manufacturing. This course is equivalent to COMP 5002 at Carleton University.

CSI 5129 Advanced Database Systems (3 units)

In-depth study on developments in database systems shaping the future of information systems, including complex object, object-oriented, object-relational, and semi-structured databases. Data structures, query languages, implementation and applications. This course is equivalent to COMP 5305 at Carleton University.

CSI 5131 Parallel Algorithms and Applications in Data Science (3 units)

Multiprocessor architectures from an application programmer's perspective: programming models, processor clusters, multi-core processors, GPUs, algorithmic paradigms, efficient parallel problem solving, scalability and portability. Projects on high performance computing in Data Science, including data analytics, bioinformatics, simulations. Programming experience on parallel processing equipment. This course is equivalent to COMP 5704 at Carleton University.

CSI 5134 Fault Tolerance (3 units)

Hardware and software techniques for fault tolerance. Topics include modeling and evaluation techniques, error detecting and correcting codes, module and system level fault detection mechanisms, design techniques for fault-tolerant and fail-safe systems, software fault tolerance through recovery blocks, N-version programming, algorithm-based fault tolerance, checkpointing and recovery techniques, and survey of practical fault-tolerant systems. This course is equivalent to COMP 5004 at Carleton University.

CSI 5135 Information Visualization and Visual Analytics (3 units)

Principles, techniques, technology and applications of information visualization for visual data analysis. Topics include human visual perception, cognitive processes, static and dynamic models of image semantics, interaction paradigms, big data visual analysis case studies. This course is equivalent to COMP 5209 at Carleton University.

CSI 5136 Computer Security and Usability (3 units)

Design and evaluation of security and privacy software with particular attention to human factors and how interaction design impacts security. Topics include current approaches to usable security, methodologies for empirical analysis, and design principles for usable security and privacy. This course is equivalent to COMP 5110 at Carleton University.

CSI 5137 Selected Topics in Software Engineering (Category E) (3 units)

Selected topics in Software Engineering (Category E), not covered by other graduate courses. Details will be available from the School at the time of registration. This course is equivalent to COMP 5900 at Carleton University.

CSI 5138 Selected Topics in Theory of Computing (Category T) (3 units)

Selected topics in Theory of Computing (Category T), not covered by other graduate courses. Details will be available from the School at the time of registration. This course is equivalent to COMP 5900 at Carleton University.

CSI 5139 Selected Topics in Computer Applications (Category A) (3 units)

Selected topics in Computer Applications (Category A), not covered by other graduate courses. Details will be available from the School at the time of registration. This course is equivalent to COMP 5900 at Carleton University.

CSI 5140 Selected Topics in Computer Systems (Category S) (3 units)

Selected topics in Computer Systems (Category S), not covered by other graduate courses. Details will be available from the School at the time of registration. This course is equivalent to COMP 5900 at Carleton University.

CSI 5142 Protocols for Mobile and Wireless Networks (3 units)

Link and network layer protocols of wireless networks; applications of wireless networks may be discussed. Topics may include: protocol implementation, mobile IP, resource discovery, wireless LANs/PANs, and Spreadspectrum. Courses CSI 6136 (SYSC 5306), CSI 5142 (COMP 5402) cannot be combined for units. This course is equivalent to COMP 5402 at Carleton University.

Precludes additional credit for SYSC 5306.

CSI 5146 Computer Graphics (3 units)

Principles and advanced techniques in rendering and modelling. Research field overview. Splines, subdivision surfaces and hierarchical surface representations. Physics of light transport, rendering equation and Bidirectional Reflectance Distribution Function. Classical ray tracing, radiosity, global illumination and modern hybrid methods. Plenoptic function and image-based rendering. This course is equivalent to COMP 5202 at Carleton University.

CSI 5147 Computer Animation (3 units)

Theories and techniques in 3D modeling and animation. Animation principles, categories, and history. Forward and inverse kinematics. Motion capture, editing and retargeting. Flexible bodies. Particle animation. Behavioral animation. Human modeling. Facial animation. Cloth animation and other sub-topics. This course is equivalent to COMP 5201 at Carleton University.

CSI 5148 Wireless Ad Hoc Networking (3 units)

Self-organized, mobile, and hybrid ad hoc networks. Physical, medium access, networks, transport and application layers, and cross-layering issues. Power management. Security in ad hoc networks. Topology control and maintenance. Data communication protocols, routing and broadcasting. Location service for efficient routing. This course is equivalent to COMP 5103 at Carleton University.

CSI 5149 Graphical Models and Applications (3 units)

Bayesian networks, factor graphs, Markov random fields, maximum a posteriori probability (MAP) and maximum likelihood (ML) principles, elimination algorithm, sum-product algorithm, decomposable and non-decomposable models, junction tree algorithm, completely observed models, iterative proportional fitting algorithm, expectation- maximization (EM) algorithm, iterative conditional modes algorithm, variational methods, applications. Courses CSI 5149 (COMP 5007), ELG 5131 (EAGJ 5131) and ELG 7177 (EACJ 5605) cannot be combined for units. This course is equivalent to COMP 5007 at Carleton University.

Permission of the Department is required.

CSI 5151 Virtual Environments (3 units)

Basic concepts. Virtual worlds. Hardware and software support. World modeling. Geometric modeling. Light modeling. Kinematic and dynamic models. Other physical modeling modalities. Multi-sensor data fusion. Anthropomorphic avatars. Animation: modeling languages, scripts, real-time computer architectures. Virtual environment interfaces. Case studies. Courses ELG 5124 (EACJ 5204), CSI 5151 (COMP 5205) cannot be combined for units. This course is equivalent to COMP 5205 at Carleton University.

CSI 5152 Evolving Information Networks (3 units)

Convergence of social and technological networks with WWW. Interplay between information content, entities creating it and technologies supporting it. Structure and analysis of such networks, models abstracting their properties, link analysis, search, mechanism design, power laws, cascading, clustering and connections with work in social sciences. This course is equivalent to COMP 5310 at Carleton University.

CSI 5153 Data Management for Business Intelligence (3 units)

Data management problems and information technology in decision making support in business environments. Topics include advanced data modeling, semantic modeling, multidimensional databases and data warehousing, on-line-analytical processing, elements of data mining, context in data management, data quality assessment, data cleaning, elements of business process modeling. This course emphasizes concepts and techniques rather than specific applications or systems/implementations. This course is equivalent to COMP 5111 at Carleton University.

CSI 5154 Algorithms for Data Science (3 units)

Algorithmic techniques to handle (massive/big) data arising from, for example, social media, mobile devices, sensors, financial transactions. Algorithmic techniques may include locality-sensitive hashing, dimensionality reduction, streaming, clustering, VC-dimension, external memory, core sets, link analysis and recommendation systems. This course is equivalent to COMP 5112 at Carleton University.

CSI 5155 Machine Learning (3 units)

Concepts, techniques, and algorithms in machine learning; representation, regularization and generalization; supervised learning; unsupervised learning; advanced methods such as support vector machines, online algorithms, neural networks, hidden Markov models, and Bayesian networks; curse of dimensionality and large-scale machine learning. Category T in course list. This course is equivalent to COMP 5116 at Carleton University.

Courses CSI 5155 , DTO 5100 , DTO 5101 , ELG 5255 , IAI 5100 , IAI 5101 , MIA 5100 , SYS 5185 cannot be combined for units.

CSI 5161 Principles of Distributed Simulation (3 units)

Distributed simulation principles and practices. Synchronization protocols: Optimistic vs Conservative, Deadlock detection in conservative simulations, Time warp simulation. Distributed interactive simulation: Data distribution management, Interest management, High Level Architectures (HLA), Run Time Infrastructure (RTI). Distributed web-based simulation. Distributed agent based simulation. Real time applications of distributed simulation. Distributed and collaborative virtual simulations. This course is equivalent to COMP 5606 at Carleton University.

CSI 5163 Algorithm Analysis and Design (3 units)

Topics of current interest in the design and analysis of computer algorithms for graph-theoretical applications; e.g. shortest paths, chromatic number, etc. Lower bounds, upper bounds, and average performance of algorithms. Complexity theory. This course is equivalent to COMP 5703 at Carleton University.

CSI 5164 Computational Geometry (3 units)

Study of design and analysis of algorithms to solve geometric problems; emphasis on applications such as robotics, graphics, and pattern recognition. Topics include: visibility problems, hidden line and surface removal, path planning amidst obstacles, convex hulls, polygon triangulation, point location. This course is equivalent to COMP 5008 at Carleton University.

CSI 5165 Combinatorial Algorithms (3 units)

Design of algorithms for solving problems that are combinatorial in nature, involving exhaustive generation, enumeration, search and optimization. Algorithms for generating basic combinatorial objects (permutations, combinations, subsets) and for solving hard optimization problems (knapsack, maximum clique, minimum set cover). Metaheuristic search, backtracking, branch-and-bound. Computing isomorphism of combinatorial objects (graphs), isomorph-free exhaustive generation. This course is equivalent to COMP 5709 at Carleton University.

CSI 5166 Applications of Combinatorial Optimization (3 units)

Topics in combinatorial optimization with emphasis on applications in Computer Science. Topics include network flows, various routing algorithms, polyhedral combinatorics, and the cutting plane method. This course is equivalent to COMP 5805 at Carleton University.

CSI 5167 Human-Computer Interaction Models, Theories and Frameworks (3 units)

A basis for graduate study in HCI with an emphasis on the application of theory to user interface design. Review of main theories of human behaviour relevant to HCI, including especially Cognitive Dimensions of Notations Framework, Mental Models, Distributed Cognition, and Activity Theory, and their application to design and development of interactive systems. This course is equivalent to COMP 5210 at Carleton University.

CSI 5168 Digital Watermarking (3 units)

Overview of recent advances in watermarking of image, video, audio, and other media. Spatial, spectral, and temporal watermarking algorithms. Perceptual models. Use of cryptography in steganography and watermarking. Robustness, security, imperceptibility, and capacity of watermarking. Content authentication, copy control, intellectual property, digital rights management, and other applications. This course is equivalent to COMP 5309 at Carleton University.

CSI 5169 Wireless Networks and Mobile Computing (3 units)

Computational aspects and applications of design and analysis of mobile and wireless networking. Topics include Physical, Link Layer, Media Access Control, Wireless, Mobile LANs (Local Area Networks), Ad-Hoc, Sensor Networks, Power Consumption optimization, Routing, Searching, Service Discovery, Clustering, Multicasting, Localization, Mobile IP/TCP (Internet Protocol/Transmission Control Protocol), File Systems, Mobility Models, Wireless Applications. Courses CSI 5169 , ELG 6168 cannot be combined for units. This course is equivalent to COMP 5304 at Carleton University.

CSI 5173 Data Networks (3 units)

Mathematical and practical aspects of design and analysis of communication networks. Topics include: basic concepts, layering, delay models, multi-access communication, queuing theory, routing, fault-tolerance, and advanced topics on high-speed networks, ATM, mobile wireless networks, and optical networks. This course is equivalent to COMP 5203 at Carleton University.

CSI 5174 Validation Methods for Distributed Systems (3 units)

Review of formal specification and description techniques for distributed and open systems. Verification techniques. Correctness proofs. Verification of general properties of distributed systems. Analysis and relief strategies. Testing techniques. Test generation strategies. Test architectures. This course is equivalent to COMP 5604 at Carleton University.

CSI 5175 Mobile Commerce Technologies (3 units)

Wireless networks support for m-commerce; m-commerce architectures and applications; mobile payment support systems; business models; mobile devices and their operating systems; mobile content presentation; security issues and solutions; relevant cross layer standards and protocols; case studies. Courses DTI 5175 , CSI 5175 cannot be combined for units. This course is equivalent to COMP 5220 at Carleton University.

CSI 5180 Topics in Artificial Intelligence (3 units)

Selected topics in Artificial Intelligence (A.I.); could include A.I. programming techniques, pattern matching systems, natural language systems, rule-based systems, constraint systems, machine learning systems, and cognitive systems. Applications could include areas in Finance, Medicine, Manufacturing, Smart Cities, Semantic Web, Healthcare, Fraud Detection, Intrusion Detection, Autonomous Vehicles, Opinion mining, Sentiment Analysis or similar areas. Assignments will be both (a) programming-oriented, requiring implementation and/or extensions of prototypes in Lisp and/or Prolog and (b) research-oriented, requiring readings of special topics in current A.I. journals. This course is equivalent to COMP 5100 at Carleton University.

CSI 5183 Evolutionary Computation and Artificial Life (3 units)

Study of algorithms based upon biological theories of evolution, applications to machine learning and optimization problems. Possible topics: Genetic Algorithms, Classifier Systems, and Genetic Programming. Recent work in the fields of Artificial Life (swarm intelligence, distributed agents, behavior-based AI) and of connectionism. This course is equivalent to COMP 5206 at Carleton University.

Precludes additional credit for COMP 4107.

CSI 5185 Statistical and Syntactic Pattern Recognition (3 units)

Topics include a mathematical review, Bayes decision theory, maximum likelihood and Bayesian learning for parametric pattern recognition, non-parametric methods including nearest neighbor and linear discriminants. Syntactic recognition of strings, substrings, subsequences and tree structures. Applications include speech, shape and character recognition. This course is equivalent to COMP 5107 at Carleton University.

CSI 5195 Ethics for Artificial Intelligence (3 units)

Students critically examine topics in applied AI ethics through the lens of contemporary philosophy and applied ethics texts, popular media articles, and technology case studies. Topics may include: bias and fairness; explainability; accountability; privacy; deception; trust/trustworthiness; and metaphors. Methods for applying ethical considerations in technology design are introduced through hands-on design projects. (Category E)

Courses CSI 5195 , DTI 5310 , DTO 5310 , SYS 5295 cannot be combined for units.

CSI 5200 Projects on Selected Topics (3 units)

CSI 5218 Uncertainty Evaluation in Engineering Measurements and Machine Learning (3 units)

Uncertainty, uncertainty propagation, Bayesian inference, sensor fusion, time series, Gaussian processes, integrating scientific/user knowledge into machine learning, neural networks for differential equations, probabilistic deep learning, sequential decision making. Case studies will be drawn from various fields including biomedical, autonomous vehicles, sensors, and signal processing.

The courses CSI 5218 , ELG 5218 cannot be combined for units.

CSI 5308 Principles of Distributed Computing (3 units)

Formal models of distributed environment; theoretical issues in the design of distributed algorithms; message and time complexity; problem solving in distributed settings. Problems discussed may include: coordination and control, information diffusion, leader election, consensus, distributed data operations, computing by mobile entities. This course is equivalent to COMP 5003 at Carleton University.

CSI 5311 Distributed Databases and Transaction Processing (3 units)

Principles involved in the design and implementation of distributed databases and distributed transaction processing systems. Topics include: distributed and multi-database system architectures and models, atomicity, synchronization and distributed concurrency control algorithms, data replication, recovery techniques, and reliability in distributed databases. This course is equivalent to COMP 5101 at Carleton University.

CSI 5312 Distributed Operating Systems (3 units)

Design issues of advanced multiprocessor distributed operating systems: multiprocessor system architectures; process and object models; synchronization and message passing primitives; memory architectures and management; distributed file systems; protection and security; distributed concurrency control; deadlock; recovery; remote tasking; dynamic reconfiguration; performance measurement, modeling, and system tuning. This course is equivalent to COMP 5102 at Carleton University.

CSI 5314 Object-Oriented Software Development (3 units)

Issues in modeling and verifying quality and variability in object-oriented systems. Testable models in model-driven and test-driven approaches. System family engineering. Functional conformance: scenario modeling and verification, design by contract. Conformance to non-functional requirements: goals, forces and tradeoffs, metrics. This course is equivalent to COMP 5104 at Carleton University.

CSI 5340 Introduction to Deep Learning and Reinforcement Learning (3 units)

Fundamental of machine learning; multi-layer perceptron, universal approximation theorem, back-propagation; convolutional networks, recurrent neural networks, variational auto-encoder, generative adversarial networks; components and techniques in deep learning; Markov Decision Process; Bellman equation, policy iteration, value iteration, Monte-Carlo learning, temporal difference methods, Q-learning, SARSA, applications. This course is equivalent to COMP 5340 at Carleton University.

CSI 5341 Learning-based Computer Vision (3 units)

Introduction to learning-based computer vision; statistical learning background; image processing and filtering primer; convolutional neural networks (CNNs), network layers, computer vision data sets and competitions; computer vision problems, in particular, image classification, detection and recognition, semantic segmentation, image generation, multi-view problems and tracking. This course is equivalent to COMP 5341 at Carleton University.

CSI 5342 Ubiquitous Sensing for Smart Cities (3 units)

Sensor and actuator networks. Dedicated and non-dedicated sensing. Vehicular sensing and smart transportation. Software Defined Things. Sensing as a service. Machine and deep learning-based misbehaviour detection. IoT-data analytics ecosystems. Federated Learning. AI-based security solutions. Auction and game theory concepts in ubiquitous sensing. This course is equivalent to COMP 5342 at Carleton University.

CSI 5343 AI-Enabled Communications (3 units)

Wireless networking fundamentals. Device to-device communications. Networking with cognitive radio. Cyber physical systems (CPS). Self-organization. Supervised and unsupervised learning. Reinforcement learning. Deep learning.This course is equivalent to COMP 5343 at Carleton University.

CSI 5344 Geometry Processing (3 units)

The course covers concepts, representations, and algorithms for analyzing and processing 3D geometric datasets. Topics include shape representations (e.g., triangle meshes, points clouds, and implicit functions), and the geometry processing pipeline covering the acquisition (e.g., with laser scanning or depth cameras), reconstruction, manipulation, editing, analysis, and fabrication (3D printing) of geometric models. This course is equivalent to COMP 5115 at Carleton University.

CSI 5345 Internet of Things (IoT) Security (3 units)

The course examines security challenges related to the Internet of Things (IoT), with a focus on consumer IoT devices, software aspects including engineering design, security of communications protocols and wireless access, cryptographic mechanisms, device integration and configuration, and security of IoT applications and platforms. This course is equivalent to COMP 5119 at Carleton University.

CSI 5346 Mining Software Repositories (3 units)

Introduction to the methods and techniques of mining software engineering data. Software repositories and their associated data. Data extraction and mining. Data analysis and interpretation (statistics, metrics, machine learning). Empirical case studies. This course is equivalent to COMP 5117 at Carleton University.

CSI 5347 Trends in Big Data Management (3 units)

Discussion of research papers on hot topics in the area of data management. The list of topics covered in the course generally spans: Data Exploration, Data Cleaning, Data Integration, Data Mining, Data Lake Management, Knowledge Graphs, Graph Processing, Question Answering, Blockchain, Crowdsourcing, Internet of Things, Text Processing, and Training via Weak Supervision. The common characteristic among all these topics is the large scale of data. This course is equivalent to COMP 5118 at Carleton University.

CSI 5350 Machine Learning for Healthcare (3 units)

Principles, techniques, technology and applications of machine learning for medical data such as medical imaging data, genomic data, physiological signals, speech and language. This course is equivalent to COMP 5113 at Carleton University.

CSI 5351 Quantum Communications and Networking (3 units)

Quantum communications and networking; the use of individual photons and teleportation to represent and transmit information. Theoretical (mathematical) principles. Practical aspects (implementation and software simulation) of quantum communications and networking. This course is equivalent to COMP 5114 at Carleton University.

CSI 5352 Internet Measurement and Security (3 units)

Measurement methodologies for understanding complex Internet phenomena and behaviors including: spread of vulnerabilities, remote network topologies, attack patterns, content popularity, Internet censorship, service quality, and adoption of security systems. Tools for efficient measurements, large-scale data analysis, stats, reproducibility of results. Ethical considerations. This course is equivalent to COMP 5500 at Carleton University.

CSI 5380 Systems and Architectures for Electronic Commerce (3 units)

E-commerce system architecture with a focus on relevant design patterns. Web servers, containers, and application frameworks. Web protocols, services, and client technologies. Scaleability through load balancing, clustering, and code optimization. Internationalization, accessibility, and privacy. Data mining and sharing approaches for digital targeted advertising. E-commerce user interface design and evaluation. Current research issues. Hands-on experience with an integrated set of current e-commerce tools. E-commerce development project. Courses EBC 5380, CSI 5380 cannot be combined for units. This course is equivalent to COMP 5405 at Carleton University.

CSI 5386 Natural Language Processing (3 units)

Overview of both rule-based or symbolic methods and statistical methods as approaches to Natural Language Processing (NLP), with more emphasis on the statistical ones. Applications such as information retrieval, text categorization, clustering, and statistical machine translation could be discussed. This course is equivalent to COMP 5505 at Carleton University.

CSI 5387 Data Mining and Concept Learning (3 units)

Concepts and techniques of data mining. Methods for data summarization and data preprocessing. Algorithms for finding frequent patterns and association analysis; classification; cluster analysis and anomaly detection. Model selection, model evaluation and statistical significance testing. Approaches for coping with Big Data. Selected applications of data mining and concept learning. This course is equivalent to COMP 5706 at Carleton University.

Permission of the Department is required. Courses CSI 5387 , DTO 5125, GNG 5125 cannot be combined for units.

CSI 5388 Topics in Machine Learning (3 units)

CSI 5389 Electronic Commerce Technologies (3 units)

Business models and technologies. Search engines. Cryptography. Web services and agents. Secure electronic transactions. Value added e-commerce technologies. Advanced research questions. Courses EBC5389, CSI5389 cannot be combined for units. This course is equivalent to COMP 5401 at Carleton University.

CSI 5390 Learning Systems from Random Environments (3 units)

Computerized adaptive learning for random environments and its applications. Topics include a mathematical review, learning automata which are deterministic/stochastic, with fixed/variable structures, of continuous/discretized design, with ergodic/absorbing properties and of estimator families. This course is equivalent to COMP 5005 at Carleton University.

CSI 5500 Projets en informatique (3 crédits)

Volet : Cours magistral

CSI 5501 Modèles formels de l'information (3 crédits)

CSI 5510 Principles de développement formel de logiciels (3 crédits)

Méthodologies pour la spécification, le développement et la vérification formels de logiciels. Utilisation d'assistants de preuves, de déduction automatisée et d'autres méthodes formelles visant l'exactitude de logiciel. Applications à la vérification de programmes et au calcul sécurisé. Ce cours est équivalent à COMP 5707 à la Carleton University.

CSI 5511 Génie de la qualité des logiciels (3 crédits)

Critères de la qualité des logiciels. Composantes et métriques de qualité. Qualité du processus de développement des logiciels. Génie de fiabilité des logiciels. Capture et validation d'exigences. Validation systématique de la conception; approche boîte-grise. Conception, implantation et gestion des tests. Étude de cas en validation et vérification des logiciels de communication. Conception orientée objet. Aspects théoriques. Ce cours est équivalent à COMP 5501 à la Carleton University.

CSI 5526 Algorithmes en bio-informatique (3 crédits)

Assemblage de l'ADN, recherche de gênes, comparaison de chaînes, alignement de séquences, structures grammaticales, structures secondaires et tertiaires. Les récents développements, tels que les puces d'ADN et de protéines. Travail additionnel requis dans le cas des étudiants inscrits sous la cote CSI 5526 .

Permission du Département est requise.

CSI 5537 Thème choisi en génie logiciel (catégorie E) (3 crédits)

Thèmes choisis en génie logiciel (catégorie E), non couverts par d'autres cours de deuxième cycle. Les détails seront disponibles à l'école au moment de l'inscription. Ce cours est équivalent à COMP 5900 à la Carleton University.

CSI 5538 Thème choisi en théorie de l'informatique (catégorie T) (3 crédits)

Thèmes choisis en théorie de l'informatique (catégorie T), non couverts par d'autres cours de deuxième cycle. Les détails seront disponibles à l'école au moment de l'inscription. Ce cours est équivalent à COMP 5900 à la Carleton University.

CSI 5539 Thème choisi en application informatique (catégorie A) (3 crédits)

Thèmes choisis en application informatique (catégorie A), non couverts par d'autres cours de deuxième cycle. Les détails seront disponibles à l'école au moment de l'inscription. Ce cours est équivalent à COMP 5900 à la Carleton University.

CSI 5540 Thème choisi en systèmes informatiques (catégorie S) (3 crédits)

Thèmes choisis en systèmes informatiques (catégorie S), non couverts par d'autres cours de deuxième cycle. Les détails seront disponibles à l'école au moment de l'inscription. Ce cours est équivalent à COMP 5900 à la Carleton University.

CSI 5555 Apprentissage machine (3 crédits)

Concepts, techniques et algorithmes en apprentissage machine; représentation, régularisation et généralisation; apprentissage supervisé; apprentissage non supervisé; méthodes avancées telles que les machines à vecteur de support, les algorithmes en ligne, les réseaux de neurones; les modèles de Markov cachés et les réseaux bayésiens; le fléau de la dimensionnalité et l'apprentissage machine à grande échelle. Catégorie T dans la liste de cours.

CSI 5561 Sujets en simulation et en optimisation des systèmes (3 crédits)

CSI 5563 Analyse et conception des algorithmes (3 crédits)

CSI 5565 Algorithmes combinatoires (3 crédits)

Conception d'algorithmes pour résoudre des problèmes de nature combinatoire (génération exhaustive, énumération, recherche et optimisation). Algorithmes pour générer des objets combinatoires de base (permutations, combinaisons, sous-ensembles) et pour résoudre des problèmes d'optimisation difficiles (knapsack, clique maximum, couverture minimum). Recherche métaheuristique, retour arrière, branch-and-bound. Calcul de l'isomorphisme des objets combinatoires (graphes), génération exhaustive sans isomorphes. Ce cours est équivalent à COMP 5709 à l'Université Carleton.

CSI 5571 Télématique : Concepts et logiciels (3 crédits)

CSI 5580 Sujets en intelligence artificielle (3 crédits)

Thèmes choisis en intelligence artificielle (I.A.); pourrait inclure des techniques de programmation en intelligence artificielle, des systèmes d'appariement de formes, des systèmes à langage naturel, des systèmes à base de règles, des systèmes de contraintes, des systèmes d'apprentissage automatique et des systèmes cognitifs. Les applications peuvent couvrir les domaines de la finance, de la médecine, de la fabrication, des villes intelligentes, du Web sémantique, de la détection de fraudes ou d’intrusion, des véhicules autonomes, de l'analyse d’opinion, de l'analyse de sentiments ou d’autres domaines similaires. Les devoirs seront à la fois (a) axés sur la programmation, exigeant l'implémentation et/ou l'extension de prototypes (b) axés sur la recherche, nécessitant des lectures de sujets spéciaux dans des revus d'I.A. contemporaines. Ce cours est équivalent à COMP 5100 à l'Université Carleton.

CSI 5780 Systèmes et architectures des logiciels pour le commerce électronique (3 crédits)

Architecture du système de commerce électronique et patrons de conception. Serveurs Web, conteneurs et cadres d'application. Protocoles, services, et technologies de client Web. Évolutivité grâce à l'équilibrage de la charge, au clustering et à l'optimisation du code. Internationalisation, accessibilité et confidentialité. Méthodes d'exploration et de partage de données pour la publicité ciblée numérique. Conception et évaluation de l'interface utilisateur pour le commerce électronique. Problèmes de recherche actuels. Expérience pratique avec un ensemble intégré d'outils de commerce électronique actuels. Projet de développement du commerce électronique. Les cours EBC 5380, CSI 5380 ne peuvent pas être combinés pour les unités. Ce cours est équivalent à COMP 5405 à la Carleton University.

Prerequisite: CSI 5389

CSI 5787 Fouille des données et apprentissage des concepts (3 crédits)

Aspects conceptuels et techniques de l’exploration des données. Méthodes pour l'agrégation et le prétraitement des données. Algorithmes d'extraction de patrons et analyse des règles d'association; partitionnement des données et détection des anomalies. Sélection et évaluation des modèles et tests de signification statistique. Approches pour composer avec les mégadonnées. Choix d'applications en exploration des données et en extraction des concepts.

CSI 5789 Technologies du commerce électronique (3 crédits)

Introduction aux modèles et technologies d'entreprise. Moteurs de recherche. Cryptographie. Services Web et agents. Transactions électroniques sécurisées. Technologies du commerce électronique à valeur ajoutée. Questions de recherche avancées. Ce cours est équivalent à COMP 5401 à la Carleton University.

Prerequisite: CSI 4110 or equivalent.

CSI 5900 Projets de recherche en informatique / Graduate Projects in Computer Science (3 crédits / 3 units)

Ce cours est équivalent à COMP 5902 à la Carleton University. / This course is equivalent to COMP 5902 at Carleton University.

Volet / Course Component: Recherche / Research

CSI 5901 Études dirigées / Directed Studies (3 crédits / 3 units)

A course of independent study under the supervision of a member of the School of Computer Science. Ce cours est équivalent à COMP 5901 à la Carleton University. / This course is equivalent to COMP 5901 at Carleton University.

CSI 5903 Stage en commerce électronique / Electronic Commerce Work Term (3 crédits / 3 units)

Expérience en milieu de travail. Noté S (satisfaisant) ou NS (non satisfaisant) selon les résultats du rapport écrit et l'évaluation de l'employeur. Préalable : être accepté au programme de certificat en commerce électronique (option technologie) et recevoir la permission du Comité du programme. / Practical experience. Graded S (Satisfactory) / NS (Not satisfactory), to be based on the grades obtained for the written report as well as on the evaluations of the employer.

Volet / Course Component: Cours magistral / Lecture

Permission du Département est requise. / Permission of the Department is required.

CSI 5904 Projet de recherche avancé en commerce électronique / Graduate Project in Electronic Commerce (3 crédits / 3 units)

Projet sur un sujet précis en commerce électronique mené sous la direction d'un professeur. Les cours CSI 5904 , CSI 5903 ne peuvent être combinés pour l'obtention de crédits. / Project on a specific topic in electronic commerce under the supervision of a professor. Courses CSI 5904 , CSI 5903 cannot be combined for units.

Exclusion: CSI 5903 .

CSI 6900 Projets de recherche intensive en informatique / Intensive Graduate Projects in Computer Science (6 crédits / 6 units)

Cours de six crédits s'échelonnant sur une période de deux sessions. L'envergure du projet de recherche exigé dans ce cours est deux fois plus grande que dans le cas de CSI 5900 . Les cours CSI 6900 , CSI 5900 ne peuvent être combinés pour l'obtention de crédits. Cours ouvert uniquement aux étudiants inscrits à la maîtrise sans thèse. Ce cours est équivalent à COMP 5903 à la Carleton University. / A two-session course. The project is twice the scope of projects in CSI 5900 . Courses CSI 6900 , CSI 5900 cannot be combined for units. Not to be taken in the thesis option. This course is equivalent to COMP 5903 at Carleton University.

CSI 7131 Advanced Parallel and Systolic Algorithms (3 units)

Continuation of CSI 5131 (COMP 5704). This course is equivalent to COMP 6100 at Carleton University.

CSI 7160 Advanced Topics in the Theory of Computing (3 units)

This course is equivalent to COMP 6601 at Carleton University.

CSI 7161 Advanced Topics in Programming Systems and Languages (3 units)

This course is equivalent to COMP 6603 at Carleton University.

CSI 7162 Advanced Topics in Computer Applications (3 units)

This course is equivalent to COMP 6604 at Carleton University.

CSI 7163 Advanced Topics in Computer Systems (3 units)

This course is equivalent to COMP 6605 at Carleton University.

CSI 7170 Advanced Topics in Distributed Computing (3 units)

This course is equivalent to COMP 6602 at Carleton University.

CSI 7314 Advanced Topics in Object-Oriented Systems (3 units)

Advanced object-oriented software engineering, in particular the issues of reuse and testing. Sample topics include: interaction modeling; class and cluster testing; traceability; design patterns and testing; the C++ standard template library. Students will carry out research. This course is equivalent to COMP 6104 at Carleton University.

CSI 7561 Études avancées en systèmes et langages de programmation (3 crédits)

Ce cours est équivalent à COMP 6603 à la Carleton University.

CSI 7900 Projets de recherche en informatique / Graduate Projects in Computer Science (3 crédits / 3 units)

Ce cours est équivalent à COMP 6902 à la Carleton University. / This course is equivalent to COMP 6902 at Carleton University.

CSI 7901 Études dirigées / Directed Studies (3 crédits / 3 units)

Ce cours est équivalent à COMP 6901 à la Carleton University. / This course is equivalent to COMP 6901 at Carleton University.

CSI 9901 Colloque / Seminar

Volet / Course Component: Séminaire / Seminar

CSI 9902 Colloque / Seminar

CSI 9997 Proposition de thèse de doctorat / Doctoral Thesis Proposal

Within 8 terms following initial registration in the program, a document, generally defining the problem addressed, relating it to the literature, outlining the hypotheses, goals, research methodology, initial results and validation approach, must be submitted to an examination committee and successfully defended. Ce cours est équivalent à COMP 6908 à la Carleton University. This course is equivalent to COMP 6908 at Carleton University.

CSI 9998 Examen général de doctorat / Ph.D. Comprehensive

A committee must be assembled and must approve at least 3 topics for written examination: typically, a major and two minor areas. An oral examination occurs if the written exam is passed. Both elements must take place within the first 4 terms following initial registration in the program. The comprehensive examination may be failed, passed conditionally (i.e., with extra course requirements) or passed unconditionally. If failed, this course may be retaken at most one time. Ce cours est équivalent à COMP 6907 à la Carleton University. This course is equivalent to COMP 6907 at Carleton University.

Undergraduate Studies

For more information about undergraduate studies at the University of Ottawa, please refer to your faculty .

Graduate and Postdoctoral Studies

For more information about graduate studies at the University of Ottawa, please refer to your academic unit .

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Simon Fraser University Engaging the World

Computing science.

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ADMISSION  

Application Deadlines

• Application deadlines for the Master of Science in Professional Computer Science Program can be found  here .

Before Applying

Before submitting an application, you should read carefully about:

• SFU's Graduate Studies Application Process  - You will need to submit your application through SFU's graduate application system, goGRAD .
• Becoming an SFU Graduate Student
• Graduate Studies Admission Requirements  for Graduate Programs
• School of Computing Science Admission Requirements
• Frequently Asked Questions about the program
• Information about Financial Support 

Application Checklist

Please note that you are required to fulfill admission requirements as laid out by both Graduate Studies and the School of Computing Science.

Admission Requirements

Admission to the graduate programs in computer science is competitive: only the best qualified applicants are offered a seat. Therefore, it is imperative that students familiarize themselves with the admission requirements in order to ensure they submit a strong application. 

The minimum requirements for admission to the doctoral program:

a) a master's degree in Computing Science or related field from Simon Fraser University or its equivalent from a recognized institution

b) The School's Graduate Admissions Committee may offer, at its discretion, PhD admission to exceptional students holding only a bachelor's degree and without a master's degree or equivalent in computer science or a related field. In this case, the student should have obtained a cumulative grade point average of at least 3.5/4.33, or a grade point average of at least 3.67/4.33 (A-) based on the last 60 units of undergraduate courses.

MSc (Thesis)

The minimum requirements for admission to the MSc (Thesis) program:

a) a bachelor's degree from Simon Fraser University or its equivalent from a recognized institution with  a cumulative grade point average of at least 3.0/4.33 (B),

b) The School's Graduate Admissions Committee may offer, at its discretion, M.Sc. admissions to exceptional students without an undergraduate degree in computer science or a related field.  Students must demonstrate, at a minimum, competence in computer science at the third year level equivalent to CMPT 300 (Operating Systems 1), CMPT 307 (Data Structures and Algorithms) and CMPT 354 (Database Systems and Structures).

MSc (Accelerated) 

The minimum requirements for admission to the MSc (Accelerated) program:

a) Students enrolled in a bachelor's degree program at SFU are qualified to be admitted into the Accelerated Master's program in the School of Computing Science provided that they have satisfactorily completed at least 90 credits of undergraduate work with a cumulative GPA of at least 3.67/4.33 including at least 24 credits of upper division CMPT course work.

b) To be admitted to the program, the student must submit evidence, usually reference letters, from qualified referees demonstrating the student’s ability to undertake advanced work in the area of interest.  Students must also satisfy typical admission requirements set by the graduate program committee.

MSc (Professional Master’s Programs)

Please visit the Professional Master's Program  admission requirements page

SFU-ZJU Graduate Dual-Degree Program (GDDP)

Applicants must be admitted to one university, and then apply and be admitted to the partner university.

To qualify for admission, students must satisfy the usual admission requirements as specified by each university. The university of first admission will be referred to as the student's 'home' university. Students whose home university is SFU are called SFU students, while those whose home university is Zhejiang University are called ZJU students.

For Masters within the GDDP with SFU as your home university, please refer to MSc (Thesis)  admissions requirements.

For PhD within the GDDP with SFU as your home university, please refer to PhD admissions requirements.

All those interested in a graduate program at SFU must complete an online application  to Graduate and Postdoctoral Studies. Each application must include all of the following:

• Online application form
• All post-secondary transcripts
• CV/Resume 
• Three letters of recommendation
• Statement of purpose
• English language competence exam results

English Language Competency

The language of instruction, examination, and communication in the professional master's program in computer science is English. Students whose primary language is not English must meet SFU's English proficiency requirements as set out in the Graduate General Regulation 1.3.3 . Applicants who have completed a degree at a recognized post-secondary institution where the language of instruction and examination is English in a country where English is the primary language are not required to submit proof of English proficiency. Please view the list of accepted countries here .

All other applicants are required to provide proof of English proficiency. For more detailed information on the requirements, please visit the Graduate Studies page on English Language Requirements .

Conditional and Qualifying Admission

In exceptional circumstances, a student may be admitted with lower formal qualifications when there is significant professional experience relevant to the proposed area of scholarship. Please do not contact us about waiving the requirement. Instead, use your application materials (your CV, statement of purpose, etc.) to make the case that your professional experience is relevant and should be considered along with your GPA.

The School's graduate admissions committee may also, at its discretion, offer admission to the program to exceptional students whose undergraduate degree is not in computer science or a related field. Such students typically make up for the lack of program-specific education through relevant work experience, course work, or certificates, diplomas, etc.

For more information on qualifying and conditional admission, please view Graduate Admissions Regulations 1.3.8  and 1.3.9

Please note: Conditional and qualifying admission is offered only in exceptional circumstances.

Decision Timeline

Admission offers are sent out on a rolling basis following the application deadline. Please note that we are unable to provide application status updates. Applicants will be notified via email once a decision has been made. All Fall applicants should receive a decision by the end of April. All Spring applicants should receive a decision by the end of November.

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Computer Science (Master's program)

Program details.

Faculty Science

Degree Master of Science

Delivery method Hybrid online/in-class

Location Ontario Tech University, North Oshawa

Start dates September, January or May

Length Approximately 24 months, based on full-time study

Program load Full-time

Program format Courses with a research thesis

The Master of Science (MSc) in Computer Science is a broad-based program that covers concepts from engineering, science and business with the aim of producing high-quality software professionals. The aim of the MSc program is to produce a new breed of computer science graduates that have a broad background in information technology along with project management and people skills. Graduates of this program will not only have strong technical expertise in their particular  field,  but will also have the ability to work effectively in interdisciplinary teams and be able to tackle problems that require both technical and non-technical solutions.

The MSc program differs from most existing computer science programs as it concentrates on both applied research and the development of professional skills. The intention is that most of the graduates from this program will build careers in industrial research and software development. The program focuses on the skills required for successful careers in industry, reflecting the university's goals to be market-oriented and to provide high-quality professional education.

The MSc program provides students with the opportunity to work in teams and develop leadership skills. Students are also given ample opportunity to develop their written and oral communication skills. MSc students are strongly encouraged to present their research results at scientific conferences.

• Digital Media Use of computer technology in the implementation of various forms of media including audio, graphics, computer animation, visual analytics, computer games and computer vision.
• Information Science Distribution and management of information including database systems, machine learning, services computing, intelligent systems and health informatics.
• Networks and IT Security Design, implementation and management of computer networks, as well as security issues such as cryptography, malware analysis and secure communications.
• Software Design Process of designing and implementing software systems, including software engineering, distributed computing, programming languages and software architecture. 
• Admission requirements
• Application deadlines
• How to apply
• Hold a four-year honours undergraduate degree in computer science, computer engineering, information technology or software engineering from a Canadian university, or its equivalent from a recognized institution.
• Minimum overall academic standing of a B (GPA: 3.0 on a 4.3 scale or 73 to 76 per cent), with a minimum B average in the last two full-time years (four semesters) of undergraduate work or equivalent.

Required supporting documents:

Please see the  checklist of required documents  for a list of supporting documentation that must be submitted with your application.

Additional requirements:

Admission depends on the availability of a research supervisor. It is recommended that applicants contact a potential supervisor before formally applying. 

In their statement of academic intent, applicants should include the type(s) of course(s) they feel they are suitable to teach as teaching assistants.

Required test scores for English language proficiency:

See  English language proficiency  for the minimum required test scores for this program.

Please see   application deadlines   for specific dates. Note that the application deadlines listed are for both the online application and all supporting documentation.

Applications for admission to all graduate studies programs are submitted online. There are five steps you must go through to complete the application process. See   application process and requirements   for step-by-step instructions.

Many of our graduate programs are extremely competitive; the number of qualified applicants normally exceeds the number of seats available for each intake. Satisfaction of minimum entry requirements does not ensure admission.

Faculty website

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Research areas

• Artificial intelligence
• Computer graphics
• Computer vision
• Data science
• Distributed computing
• Health informatics
• Information visualization
• Network design
• Network security
• Serious games
• Software engineering
• Ubiquitous computing
• Virtual reality

Learn more about the research areas within this program and find research experts by visiting the faculty’s website and the university's Expert Centre .

Additional information

Internal awards and funding.

Applicants to research-based graduate programs who are studying full-time are automatically considered for some types of funding at the time of admission.

Types of funding that do not require an application:

• Entrance scholarships
• Minimum funding packages
• Teaching assistantships, research assistantships and graduate research assistantships

For more details on the above funding opportunities, see   graduate student awards and funding .

Please note:   Part-time students are not eligible for the above funding opportunities.

External awards and funding

Graduate program applicants are encouraged to apply for   external awards   to help finance their education. The application process differs for each competition, so review the information carefully to determine where and when you must apply.   Please note:   The majority of these awards are for domestic or permanent residents only.

Tuition fees for graduate programs are charged on a flat-fee or fee-per-credit basis and vary by program and student status.

For current, specific fees and details on flat-fee versus fee-per-credit programs, please see   tuition and fees .

Contact the program:

Faculty of Science 905.721.3050 [email protected]

Contact the School of Graduate and Postdoctoral Studies:

905.721.8668 ext. 6209 [email protected]

Master's Program

The Department of Computer Science boasts twelve different research groups with cutting-edge facilties and technology. The diverse research interests of our faculty attracts graduate students and researchers from all over the globe. Our research groups produce world-renowned papers and advancements, and contribute to the ever growing exploration of computers and technology. Graduate students also have the opportunity to collaborate with relevant industry partners. The Department of Computer Science has a strong graduate program and is one of the highest recruiting research groups on campus. We typically have ~150 graduate students enrolled in both M.Sc. and Ph.D. programs.

The MSc in Computer Science and MSc in Applied Computing programs accept students with at least a four-year undergraduate degree, or equivalent, from any recognized college or university. These program requirements and the method of admission are described below. Furthermore, there is an additional opportunity that is only available for students who are in the process of completing a four-year Honours BSc in either Computer Science or Applied Computing from the University of Saskatchewan. This opportunity will make it feasible to finish the MSc in Computer Science in as little as 12 months after finishing their undergraduate degree at the University of Saskatchewan by gaining research experience while they are still undergraduate students. This is called the Accelerated Master’s Admission Pathway . Details and a description of the admission process for this pathway are on a separate page .

Program of Study - Computer Science

The Master’s in Computer Science program is a thesis-based M.Sc program with an expected length of 20 months.

The following summarizes the requirements as outlined in the Graduate Calendar, for a fully qualified M.Sc. candidate's program of study in Computer Science. The program usually consists of: four half-year classes amounting to 12 credit units, at the graduate level, from the field in which the student is working; a thesis permitting the student to make some contribution to knowledge; and seminars, colloquia and related activities as the student's department may require. These regulations are interpreted as follows for Computer Science:

•  Completion of at minimum four courses numbered between 810 to 879, or numbered 898, as determined by the advisory committee. At most one class that is not a "CMPT" course is permitted.
• Three (3) credit units may be taken at the 300 level or 400 level, as approved by the Advisory Committee.
• The student must fulfill a residency requirement of at least 8 months. Residency is defined as living in, or near Saskatoon, regular attendance on campus, regular interaction with the student's supervisor, and participation in the affairs of the student's research lab and/or of the department.
• Students must regularly attend the CMPT 990 seminar series during the period of their residency.
• Completion of an M.Sc. thesis, designated as CMPT 994, that makes a practical or theoretical contribution to Computer Science.
• Completion of the GSR 960 ethics course.

It is the student's responsibility to ensure all requirements of the Program of Studies have been completed, registration is current, outstanding fees are paid, and University deadlines are met for convocation.

Program of Study - Applied Computing

The Master’s in Applied Computing program is a thesis-based M.Sc program with an expected length of 20 months.

The following summarizes the requirements as outlined in the Graduate Calendar, for a fully qualified M.Sc. candidate's program of study in Applied Computing. The program usually consists of: four half-year classes amounting to 12 credit units from the field in which the student is working; a thesis permitting the student to make some contribution to knowledge; and seminars, colloquia and related activities as the student's department may require. These regulations are interpreted as follows for Applied Computing:

• At least six (6) credits worth of graduate-level coursework numbered between 810 to 879, or numbered 898, must be from the Department of Computer Science (CMPT prefix).
• The remaining six (6) credit units can be from the cognate discipline(s), as approved by the Advisory Committee.
• Completion of an M.Sc. thesis, designated as CMPT 994, that makes a practical or theoretical contribution applying Computer Science to a cognate area.

Continuous Registration

Graduate students are required to maintain continuous registration in certain courses until their program is complete. There are three terms for all graduate students: Term 1: Regular Session (September - December) Term 2: Regular Session (January - April) Term 3: Spring/Summer Session (May - August)

Policies and Procedures for Graduate Students

Sections of the CGPS policies manual that are most relevant to current graduate students are summarized and paraphrased below. The CGPS Policies and Procedures manual remains the authoritative document for these rules and regulations. 1. Advisory Committees ( CGPS Policies Manual )  As soon as possible following a student's first registration in his or her program, an Advisory Committee, including research supervisor, should be named. It is the responsibility of the Advisory Committee to assist in course selection and definition of research area, provide support and advice, regularly evaluate the student's progress by meeting at least once yearly, to take appropriate and timely action in view of this progress, and to keep records of this evaluation and all actions taken.   An M.Sc. advisory committee must consist of:

• the graduate chair or designate, as advisory committee chair;
• the supervisor(s); and
• at least one additional member – for students in Applied Computing, this member can be from the cognate discipline.

Annual Review of Status

In compliance with CGPS policy, the Graduate Committee meets annually to review the status of every graduate student registered in Computer Science. Prior to this meeting, a report is prepared by each graduate student's supervisor outlining the progress of that student towards his or her degree. This information, along with other indicators of the student's performance (i.e. marks in courses, steps taken en route to thesis completion, etc.), is examined and a decision is made on whether or not that student is making acceptable progress in the graduate program. If a student so chooses, he or she may write a short document outlining concerns he or she may have, and this will be added to the information used by the Committee. This document will be kept confidential, even from someone on the Committee, should the student desire. This checkpoint should be taken very seriously by both students and faculty members, and every effort should be expended by students to complete courses, and by faculty members to get all marking done, before this meeting so that the student's record is as complete as possible.

Scheduling Your Thesis Defence

Pre-defence Meeting

Before a thesis may be scheduled for defence, your advisory committee must have a meeting to approve your thesis for defence. For M.Sc. degrees, an email vote is sufficient. A thesis may not be released to the external examiner until the advisory committee approves the thesis for defence.

Appointment of the External Examiner

As part of your pre-defence meeting, your advisory committee must determine the name of a potential external examiner. For M.Sc. degrees, the external examiner must be from another department within the university.   The external examiner must have an "arm's length" relationship with the student, supervisor and members of the advisory committee. For detailed information on selection of external examiners, and selection criteria for external examiners, see the CGPS policies manual . Upon receipt of the suggestion for the external examiner the graduate program assistant will forward the name to the College of Graduate and Postdoctoral Studies (CGPS) for approval.

*The student must not send a copy of the thesis to the external examiner.  This is handled by the supervisor or graduate program assistant. Scheduling the Oral Examination (Thesis Defence)

Once the external examiner has been approved, the thesis defence can be scheduled. The graduate program assistant or student's supervisor will schedule a date and time at which all examiners are available. Students must not contact the external examiner. Sufficient time must be allowed so that the graduate program assistant can send the paperwork to CGSR at least 3 weeks before the desired defence date. For full details, see the CGPS policies manual .

Preparing Your Thesis Document

The Writing Process and Thesis Structure

The production of a thesis is the culmination of any graduate program. The research embodied in the thesis and the actual writing of the document are essential elements of graduate training. Long after course work and term papers are forgotten, the thesis endures as a lasting record of a graduate student's accomplishment. With that in mind, we offer some suggestions on how to approach this challenging task. The proper presentation of thesis work is very important. The key to good presentation is organization and clarity. Just as a properly organized computer program is the result of applying a methodology during program development, a properly organized thesis is the result of applying a methodology when developing the thesis. A top-down approach using iterative refinement is as applicable to the writing of a thesis (or a paper) as it is to the design of computer systems. A preliminary outline is expanded to a detailed outline, and then to initial drafts of each of the subsections. Each chapter, section, and subsection should have an introduction (stating the content and purpose), a body, and a conclusion (summarizing the important points presented and possibly establishing a lead-in to the next unit). It is wise to review each thesis chapter, possibly with your thesis supervisor, at each level of refinement. The end product of such a process is almost always more understandable than starting at page one and writing until a final page becomes necessary. Writing Style

Clarity is very important in scientific writing. Although clarity cannot be equated to simplicity, there is certainly a high degree of correlation. Since the material you are presenting is of a highly technical nature and is difficult enough to understand, the use of highly complex sentence structures will add little to the comprehensibility of a paper or a thesis. Unless you are particularly adept with prose, simple straightforward sentence structures are recommended. A number of commonly accepted rules for good writing style should be followed (for example, always write in the present tense and avoid writing in the first or second person). Most students would benefit from reading some books on the subject of writing style available in the library or bookstore (for example, A Manual for Writers by Kate L. Turabian or The Elements of Style by W. Strunk and E. B. White). A Handbook for Scholars by Mary-Claire van Leunen is recommended as an excellent guide to the technical issues of form. Another useful publication is the Chicago Manual of Style from the University of Chicago.

The format of a thesis is also important, and it is the student's responsibility to ensure that the correct format is followed. In particular, attention should be given to matters such as title page, table of contents, abstract, list of figures, list of tables, footnotes, quotations, figure captions, table captions, references and citations, and appendices. Each department maintains certain conventions within the guidelines set out by the College of Graduate and Postdoctoral Studies (see the guidelines for thesis preparation , available on-line at the College of Graduate and Postdoctoral Studies web site). It is suggested that previous theses from the Department be examined for guidance. While the use of the computer-based text-processing facilities is encouraged for thesis preparation, the use of such facilities do not provide license for you to depart from acceptable standards--especially with respect to the production and placement of figures and tables, headings, margin size, or the size of print. Theses may be produced in either the traditional style or the ‘manuscript’ style, which consists of a manuscript, or cohesive series of manuscripts, written in a style suitable for publication in appropriate venues. Details and guidelines for manuscript-based theses are available at CGPS , and it is required that these guidelines be followed. Note that a manuscript-style thesis requires permission of the Advisory Committee. A manuscript-style thesis must meet the same rigorous academic standards as a traditional thesis. It is expected that the author of the thesis will be the primary author on at least one manuscript included in the thesis. One manuscript is the minimum for a manuscript-style M.Sc. thesis.

These document templates will assist in the production of a thesis document that corresponds to CGPS rules for thesis formatting. • LaTeX Template (on the Computer Science Department LaTeX page) • Microsoft Word Templates (provided by CGPS)

What to Expect at Your Thesis Defence

The thesis defence is an oral examination, open to all interested members of the department. Your examining committee will consist of your advisory committee plus an external examiner, and any other members of the faculty that are considered necessary.  A thesis defence follows the following general format, but may deviate at the discretion of the chair of the examining committee.

Presentation

You will begin the thesis defence with a short, 10-20 minute presentation that summarizes the major contributions of the thesis.

Beginning with the external examiner, each of your examiners will be given the opportunity to ask you questions. These questions may be very general in nature, testing the breadth of your knowledge, or may be very specific in nature, testing the depth of your knowledge. After each examiner has had their turn, additional rounds of questions may be conducted as needed, as determined by the examining committee chair.

Deliberation

At the conclusion of the examination, you will be asked to leave the room while the examining committee discusses your oral examination and your written thesis, and decides upon an outcome. Upon conclusion of these deliberations, you will be called back into the room and informed of the results. 

After the Defence

If your thesis is accepted, you will need to make any corrections/revisions that your examining committee deems necessary. You will be required to submit an electronic copy of the final, corrected, and revised copy of your thesis to the ETD site of the University of Saskatchewan. You are also asked to submit a bound copy to be kept in the Department of Computer Science. In addition, it is customary to offer bound copies to each member of your examining committee. Finally, you will need to complete an online application to graduate . This is the student's responsibility.

• How to Apply

Computer Science

Master of Science (M.Sc.) Doctor of Philosophy (Ph.D.)

Research supervisors

Tuition and funding, admission requirements, application process.

The deadline to apply if you wish to start in September is January 10.

The master's and doctoral programs in computer science offer students high quality, cutting-edge research opportunities and supervision by world leaders in their respective fields. Graduates of our program have gone on to work for industry leading companies such as HP Labs and Pixar Animation Studios.

Our master's program is ideally suited to students wishing to become senior professionals in the technology industry or to those seeking to prepare for a career in scientific research. Graduates of this program often become senior programmers or project leaders at companies that develop commercial software or game design studios.

Our doctoral program provides students with intensive training in the scientific enterprise for those wishing to pursue academic or industrial research careers. Graduates of this program are qualified to seek positions in the research and development units of large technology companies or to pursue independent research careers as university professors.

It is not necessary to find a potential supervisor before you apply to this program. However, you can list three preferred supervisors which can indicate an interest in working with those individuals. Permission does not need to be obtained from these potential supervisors beforehand, and it merely signifies interest.

• Faculty websites
• Research groups

[email protected] Faculty website

Research interests:

• Accessibility
• Software Engineering
• International Standards

Zadia Codabux

Assistant professor.

[email protected] Faculty website

Areas of specialization

Empirical Software Engineering; Technical Debt; Software Metrics; Predictive Analytics (incl. Data Mining, Machine Learning); Software Quality

Ralph Deters

[email protected] Faculty website

Apps; Blockchain; Cloud Computing; Internet of Things; cloud; distributed systems; mobile; semantics; wireless sensor

• Internet of Things (IoT)
• Scalability & Dependability of Distributed Systems
• Apps & Mobile Computing
• Cloud Computing
• Semantic Web
• Multi-Agent Systems

Christopher Dutchyn

Associate professor.

[email protected] Faculty website

game semantics; language; programming; semantics; type theory

• Programming languages
• Aspect-oriented programming
• Multi-core computation
• Computational reflection
• Compilers and interpreters

Derek Eager

[email protected] Faculty website

content delivery; internet; multimedia; networks; video

• Computer system performance evaluation and modeling
• Distributed computer systems
• Computer networks
• Internet content distribution
• Internet multimedia applications

Mark Eramian

[email protected] Faculty website

computer vison; image processing; medical imaging; segmentation

• Image Processing
• Computer Vision
• Image Segmentation
• Deep Learning Learning Applications in Computer Vision
• Image-based Plant Phenotyping
• Human factors in Image Annotation and Segmentation Evaluation

Carl Gutwin

[email protected] Faculty website

cooperative; human computer interaction; interaction; surface computing; video games

• Computer-supported cooperative work
• Interaction techniques
• Surface computing
• Human Computer Interaction

Nadeem Jamali

[email protected] Faculty website

AI; Actors; Artificial Intelligence; Concurrency; Distributed systems; Parallel systems; Programming Languages; cloud; coordination; green computing; grid computing

• Parallel and Distributed Systems
• Programming Languages
• Artificial Intelligence

Lingling Jin

[email protected] Faculty website

bioinformatics; comparative genomics; computational genomics; formal language and automata theory; natural computing; plant genome evolution

• bioinformatics
• computational genomics
• comparative genomics
• plant genome evolution
• natural computing
• formal language and automata theory

Matthew Links

[email protected] Faculty website

Genomics, Bioinformatics, Microbiome

Dwight Makaroff

[email protected] Faculty website

data processing; data storage; energy efficiency; mobile devices; multiplayer; operating systems; security; wireless networks

• Distributed Data Processing architectures and performance
• Network and OS Support for multi-player online games
• Information-centric networking
• Energy efficiency in mobile devices
• Multicore architectures and application performance
• Security and intrusion issues in wireless networks, especially mesh networks and sensor networks
• Distributed data storage and retrieval
• Web usage analysis, performance of web-based systems

Ian McQuillan

[email protected] Faculty website

automata theory; bioinformatic; computational models; genetics; information visualization; theoretical computer science

• Bioinformatics
• Natural Computing
• Formal Language and Automata Theory
• Theoretical Computer Science
• Information visualization
• Computational models of genetic systems

Debajyoti Mondal

[email protected] Faculty website

Algorithm Design and Analysis; Big Data Analytics; Computational Geometry; Graph Drawing and Networks; Information Visualization

• Information Visualization
• Graph Drawing and Networks
• Algorithm Design and Analysis
• Computational and Discrete Geometry

Eric Neufeld

, biomedical.

[email protected] Faculty website

artificial intelligence; graphics; medical models; mobile computing; visualization

• Uncertainty in Artificial Intelligence
• Mobile computing
• Anatomical Visualization - building software for visual models of organs that could be measured for medical purposes

Nathaniel Osgood

[email protected] Faculty website

epidemiology; informatics; mathematical modelling; monitoring; public health

• Computational and Mathematical Modeling and Toolbuilding in support of Public Health
• Computational Epidemiology
• Public Health Informatics
• Understanding of population health trends and health policy tradeoffs
• Design more effective screening or treatment strategies for an illness
• Smartphone-based iEpi epidemiological monitoring system

Mrigank Rochan

[email protected]

Machine Learning, Computer Vision

Assistant Professor (Tenure-track)

[email protected] Faculty website

Interactive Software Engineering; Program Comprehension; Software Analytics

• Software Maintenace and Evolution
• Reverse Engineering
• Empirical Software Engineering
• Program Comprehension
• Scientific Workflow Management System
• Software Architecture
• Software Analytics
• Big Data Analytics

Chanchal Roy

[email protected] Faculty website

clone detection; engineering; programming; software

• Software engineering
• Software maintenance and evolution
• Clone detection and analysis,
• Empirical software engineering
• Program comprehension
• Mining Software Repositories

Kevin Schneider

[email protected] Faculty website

human computer interaction; languages; modeling; simulation; software; visualization

• Software Research
• Software Architecture and Design
• Software Evolution and Maintenance
• Software Analysis and Navigation
• Software Visualization, Simulation and Modeling
• Forward and Reverse Engineering
• Domain Specific Languages

Ray Spiteri

[email protected] Faculty website

high-performance computing; mathematics; optimization; problem solving; software

• Numerical analysis
• Scientific computing and software
• High-performance computing
• Optimization
• Industrial mathematics and problem solving

Natalia Stakhanova

[email protected] Faculty website

Malware analysis & attribution; Software obfuscation & reverse engineering; Mobile security; Web browser security

Ian Stavness

[email protected] Faculty website

3D displays; 3D models; aerial imaging; biomechanics; biomedical; computer graphics; human computer interaction; medical imaging; plant phenotyping

• Deep Learning & Computer Vision
• Computer Graphics, Modeling & Simulation
• Computational Agriculture
• Computational Medicine
• 3D Displays

Julita Vassileva

[email protected] Faculty website

decentralized architectures; multi-agent systems; personalization; persuasive technology; privacy; social computing; user modeling; visualization

• Personalization, User Modeling, Recommender Systems,Explainable AI
• Social Computing, Incentive Mechanisms, Persuasive Technologies
• Social Personalized Learning Environments, Peer-help, Learning Communities
• Decentralized Social Architectures, Peer-to-Peer and Multi-Agent Systems
• Trust and Privacy, Trust and Reputation Mechanisms

All applicants to both the Computer Science and the Applied Computing graduate program are automatically considered for financial support. The funding system for all students admitted to start in September 2024 or later is as follows:

M.Sc. students are normally funded for 20 months (the expected program length, with funding ending early if the student finishes earlier than 20 months) at a rate that covers the tuition/year at the time of admission plus an additional $18,000/year. Specifically, in the first 12 months of the program, they will receive enough to cover tuition plus $18,000, and in the next 8 months, they will receive enough to cover 8 months of tuition at the time of admission plus $12,000. Even though International Master's tuition rates are higher than domestic tuition, the funding package pays the difference as part of a fund called the International Student Tuition Offset Bursary.

Ph.D. students are normally funded for 4 years (the expected program length) at a rate that covers the cost of tuition per year at the time of admission plus $20,000/year.

Some sources of funding require that the student have a GPA of at least 80% at the time of admission and to maintain a GPA of at least 75% for the duration of their funding period. Most students will be required to provide service hours to the department as a lab instructor or marker.

Prospective applicants are strongly encouraged to apply for external funding such as an NSERC postgraduate scholarship. All students who are awarded an NSERC ( CGS-D , CGS-M ) or Vanier scholarship, and attend the Department of Computer Science at the University of Saskatchewan will receive an additional $6,000 annual top-up scholarship from the College of Graduate and Postdoctoral Studies for each year that they hold the award. Furthermore, after the award is finished, they will continue to receive funding from the Department of Computer Science for the remainder of their funding term as listed above. For example, if a student is awarded an NSERC CGS-M award listing the University of Saskatchewan as an institution where they could hold the award, and they are admitted and attend the Department of Computer Science at the University of Saskatchewan, they will receive $17,500 from NSERC plus a $6,000 top-up from the College of Graduate and Postdoctoral Studies for their first year; and will receive normal funds from the Department of Computer Science in their second year.

Thesis or project-based master's program

Graduate students in a thesis or project-based program pay tuition three times a year for as long as they are enrolled in their program.

Doctoral program

Doctoral students pay tuition three times a year for as long as they are enrolled in their program. Both international and domestic Ph.D. students pay the same rate.

Student fees

In addition to tuition above, students also pay fees for programs like health and dental insurance, a bus pass, and other campus services. The amount you need to pay depends on if you are taking classes full time or part time, and if you are on campus or not. The table below assumes you are on campus full-time.

Tuition information is accurate for the current academic year and does not include student fees. For detailed tuition and fees information, visit the official tuition website .

Master of Science (M.Sc.)

• Language Proficiency Requirements : Proof of English proficiency may be required for international applicants and for applicants whose first language is not English. A minimum overall TOEFL score of 94 is required, or a minimum overall IELTS score of 7.0, or a minimum overall Duolingo English Test score of 120, or another approved test as outlined in the College of Graduate and Postdoctoral Studies  Academic Policies .
• A cumulative weighted average of at least a 70% (USask grade system equivalent) in the last two years of study (e.g. 60 credit units)
• A four-year honours degree, or equivalent, from a recognized college or university in an academic discipline relevant to the proposed field of study
• Demonstrated ability for independent thought, advanced study, and research

Doctor of Philosophy (Ph.D.)

• Language Proficiency Requirements : Proof of English proficiency may be required for international applicants and for applicants whose first language is not English. A minimum overall TOEFL score of 94 is required or a minimum overall IELTS score of 7.0, or a minimum overall Duolingo English Test score of 120 or another approved test as outlined in the College of Graduate and Postdoctoral Studies  Academic Policies .
• Master's degree, or equivalent, from a recognized university in an academic discipline relevant to the proposed field of study
• A cumulative weighted average of at least a 70% (USask grade system equivalent) in the last two years of full-time study (e.g. 60 credit units)

Note that these English language proficiency requirements supersede the minimum requirements of the College of Graduate and Postdoctoral Studies . Furthermore, the Department of Computer Science does not use the WHED database to exempt students if the primary language of instruction at their previous institution was in English, and the Department of Computer Science does not accept letters from universities stating the medium of instruction is English. However, test exemptions may be possible in certain circumstances; please contact [email protected] to inquire.

Submit an online application

Before beginning your online application, be sure that you have carefully reviewed all program information and admission requirements on this page.

During the application, you'll be asked for:

• Personal information such as your name, address, etc.
• For your letters of recommendation, two of your referees must be academic contacts, and the third may be academic or professional
• Your complete academic history from all previous post-secondary institutions
• Other information requested by the Department of Computer Science

The application takes about 30 minutes to complete. You may save your application and return to it later.

At the end of the application, you will need to pay a non-refundable $120 application fee. Your application will not be processed until payment is received .

• Begin an application
• Detailed application instructions

Submit required documents

Once you've completed an online application, you will need to upload the following documents :

Transcripts

Preliminary Statement of Marks

• Once you have submitted your application for admission and paid the application fee, you will be required to upload unofficial PDF copies of your academic transcript(s) from each post-secondary institution attended. This requirement will appear as Preliminary Statement of Marks or Additional Prelim. Statement under admission requirements on your Application Summary when you  check your application status .
• The uploaded transcript can be an unofficial copy of the transcript issued by the university or college, and must include a grading key/legend.
• All pages of a transcript must be uploaded as a single PDF document.
• Uploaded transcripts will be considered unofficial or preliminary. Official copies of your transcripts will be required only for applicants offered admission. This requirement will appear as Post-secondary Transcript under admission requirements on your Application Summary when you  check your application status .
• Uploading documents

Post-secondary Transcripts

If you receive an offer of admission, you will then be required to have your official post-secondary transcripts sent (by mail in a sealed envelope directly from the institution) to the address below. Please do not send official documents until we request them.

College of Graduate and Postdoctoral Studies Room 116 Thorvaldson Building, 110 Science Place  Saskatoon, SK CANADA S7N 5C9

• Transcripts usually indicate the institution’s name, grading scheme (typically on back of transcript), your name, course names, numbers, credits, and the grades you have received. Depending on the country or institution, some features may not be available.
• Transcripts in languages other than English must be accompanied by a certified translation.
• If you are a current University of Saskatchewan student completing your undergraduate program then a letter of completion of degree requirements will be required from your college.

Proof of English language proficiency (if required)

Proof of English language proficiency may be required for international applicants and for applicants whose first language is not English. The Department of Computer Science has additional English requirements beyond the University minimum requirements.

For students who are required to provide proof of English proficiency:

• It is your responsibility to have completed an official and approved test with the appropriate score before the application deadline.
• Tests are valid for 24 months after the testing date and must be valid at the beginning of the student's first term of registration in the graduate program.
• Applicants will be required to upload a PDF copy of any required language test score. Uploaded test scores will be considered unofficial or preliminary.

If you receive an Offer of Admission you may be required to have your official language test scores sent to the address below. Please do not send official documents until we request them.

College of Graduate and Postdoctoral Studies Room 116 Thorvaldson Building - 110 Science Place Saskatoon, SK CANADA S7N 5C9

A curriculum vitae or resume

• Your curriculum vitae or resume should be a one or two page concise summary of your skills, experience and education.
• A curriculum vitae or resume is essentially your full academic and professional profile. It should include a summary of your educational and academic backgrounds as well as teaching and research experience, publications, presentations, awards, honours, affiliations and other details.
• Applicants will be required to upload a PDF copy of their curriculum vitae or resume.

Research statement

You must download and fill out the Supplemental Application form , which is your research statement. Save it as a PDF and upload it once it is complete.

Thesis Abstract for Ph.D. applicants only

Additional requirements can be found on the Department of Computer Science's Applications for admission page.

• After you've applied

176 Thorvaldson Bldg. 110 Science Place University of Saskatchewan Saskatoon, SK S7N 5C9

Graduate Chair Ian McQuillan Email: [email protected]

Graduate Administrator Maurine Powell Email: [email protected]

• Department of Computer Science Learn more about the academic unit offering this program
• Program and Course Catalogue To view official admission and program requirements

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Khoury College of Computer Sciences

Computer science.

Are you a software engineer, software development engineer, related computer science professional, or recent CS graduate looking to make your next career move? Prepare to take on new projects, learn new technologies, hold a leadership role, and help advance the field of computer science in a program known for industry connections and diverse work opportunities.

Experience more. The Master of Science in Computer Science (MSCS) at Northeastern University’s Khoury College of Computer Sciences prepares computer science (CS) professionals in approximately two years to tackle diverse challenges and build the latest technologies. Refine your knowledge and gain expertise in three breadth areas: 1) systems and software, 2) theory and security, and 3) artificial intelligence and data science.

• Prepare for more complex roles, research, or specialized positions with your current company—or take part in experiential co-op and internship opportunities with one of our 700+ partner companies
• Increase your earning potential with a degree from Northeastern, an R1 research institution
• Contribute to the dynamic field of CS with innovative project work across industries

Develop your professional network in Vancouver

Northeastern’s Vancouver campus is located on the beautiful Vancouver Harbor waterfront. It shares a building with the regional headquarters for Deloitte and Apple, is across from Amazon, and is alongside the region’s largest tech employers—and the city’s vibrant startup tech community.

Vancouver is buzzing with spinoff companies, startup incubation, technology licensing, and commercialization. Vancouver’s tech sector is strong in research and development. The city leads in virtual reality, augmented reality, AI, robotics, information and communication technology, SaaS, and gaming. Vancouver also offers great opportunities in communications, medicine, pharmaceutical sciences, and more. 

Learn More About Vancouver Campus

More Details

Unique features.

• Opportunities for paid, full-time co-ops or internships with diverse organizations like Microsoft, SAP, Providence Healthcare, Royal Bank of Canada, Clio, Think Technologies, Nextech AR Solutions, and more
• Work with world-leading multinational corporations, creative startups disrupting entire industries, diverse companies within a fast-growing hub for frontier technologies (VR, AR, computer vision, AI, drones, robotics), and members of the world-renowned global information and communications technology (ICT) sector 
• Interdisciplinary curriculum incorporates elements of web development, network security, and machine learning
• Faculty with connections to diverse employers in Vancouver and across Canada such as Calgary Scientific Inc., Electronic Arts, the Federal Aviation Administration, Malaspina Labs, MetaOptima Technology, Mio Global, the National Institute of Informatics, Nextech AR Solutions, Nuance, Schneider Electric, Synaptitude Brain Health, and more

Career Outlook

Positions requiring a master’s in computer science are expected to have a job growth rate of +22%, compared to the average job growth rate of 7–8% (2020–2030, USBLS).

The top employer of graduates of the MSCS program is Amazon. Our graduates also find employment with companies like Google, Meta, Microsoft, F5, Nordstrom, GoDaddy, McKinsey, Zillow, Snowflake, Salesforce, Carfax, and Coinbase.

MSCS program graduates hold positions such as:

• Software development engineer
• Software engineer
• Full-stack developer

Industry-aligned Program

Develop expertise across three breadth areas: systems and software, theory and security, and artificial intelligence and data science. You’ll choose from a range of electives to tailor your program to your interests.

Master’s core courses:

• Programming Design Paradigm

Electives in a range of areas:

• Artificial Intelligence
• Computer-Human Interface
• Data Science
• Game Design
• Information Security
• Programming Languages
• Software Engineering
• Theory 

For International Students 

This program is eligible for a Canadian Study Permit and Post Grad Work Permit (PGWP). For more information on studying in Canada—including how to apply for a Study Permit—please visit our  Office of Global Services’ Canadian Campuses page .

Looking for something different?

A graduate degree or certificate from Northeastern—a top-ranked university—can accelerate your career through rigorous academic coursework and hands-on professional experience in the area of your interest. Apply now—and take your career to the next level.

Program Costs

International Students Tuition rate for International (Non-Canadian Resident) $50,016 CAD

Paying for the MSCS program We offer a variety of resources, including scholarships and assistantships.

Requirements

• Online application and application fee
• The Foreign Credential Evaluation (FCE) is a required assessment of all transcripts and documents from non-U.S. accredited post-secondary education institutions. (Review the FCE requirements by country.)
• Statement of purpose that should include career goals and expected outcomes and benefits from the program
• Recent professional resumé listing detailed position responsibilities
• Three letters of recommendation
• GPA minimums: 3.0 on a 4.0 scale, 8.0 on a 10.0 scale, or 80 on a 100 scale
• Official TOEFL (100 minimum) or IELTS (7.5 minimum) examination scores (international students only)
• GRE Optional

Questions?: [email protected]

View full application instructions .

Are you and International Student? Learn more about applying for a Canadian Study Permit

Global Engagement Learn how our teaching and research benefit from a worldwide network of students, faculty, and industry partners.

Admissions Dates

Applicants must submit the online application and all required admission materials no later than the stated deadlines to be considered for admission. Admissions decisions are made on a rolling basis.

Industry-aligned courses for in-demand careers.

For 100+ years, we’ve designed our programs with one thing in mind—your success. Explore the current program requirements and course descriptions, all designed to meet today’s industry needs and must-have skills.

View curriculum

Your curriculum is designed to give you advanced theoretical knowledge that you can immediately apply to real-world situations. Experiential learning takes place in the form of project work, research opportunities, and paid co-op and internship opportunities.

Explore the junctions of computer science and entertainment, media, business, finance, communications, medicine, pharmaceutical sciences, and more. Think about AI in the context of accessible game design. Research neural networks with the capability to calculate the origins of an epidemic. Make a difference in your work.

Experiential Learning in Vancouver

Research at Northeastern

Get a roadmap to reach your goals

Your experiential opportunities are closely integrated with both your course curriculum and the advising system. Our career services staff will support you in finding and succeeding in your experiences. A team of academic advisors will also help guide you.

Our Faculty

Northeastern University faculty represents a broad cross-section of professional practices and fields, including finance, education, biomedical science, management, and the U.S. military. They serve as mentors and advisors and collaborate alongside you to solve the most pressing global challenges facing established and emerging markets.

Bethany Edmunds

By enrolling in Northeastern, you’ll be connected to students at our 13 campuses, as well as 300,000-plus alumni and more than 3,500 employer partners around the world. Our global university system provides you with unique opportunities to think locally and act globally and serves as a platform for scaling ideas, talent, and solutions.

Related Articles

Is a Master’s in Computer Science Worth the Investment?

How to Choose a Computer Science Specialization

Northeastern’s MS in Computer Science Curriculum

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Computer Science

• Requirements
• Fees & Funding
• How to Apply

Program Type

• Master of Science in Computer Science (MSc)
• Master of Science in Computer Science (MSc) - Co-operative Option

The application is closed to International applicants. 

You will need to provide your unofficial documents: final transcript, proof of graduation, CV, Statement of Purpose, proof of English language, and the Computer Science Background Form.

Computer Science combines the intellectual challenge of a young discipline with the excitement of an innovative and rapidly expanding technology.  

Computer science has been an active area at Lakehead University for over 25 years. The department resides in the University's Advanced Technology and Academic Centre ( ATAC ), a striking building that houses many of the University’s computing activities. Faculty, staff, and students are equipped with state-of-the-art computing facilities including smart lecture rooms, labs, and a variety of computing technologies (e.g. Virtual Reality, Parallel Computing).

The Master's program in computer science provides an opportunity to explore the breadth and depth of advanced knowledge in the discipline. Students benefit from a selection of advanced courses and a chance to pursue research that aligns with their interests and aspirations.

Three program options are available to students:

• Master’s by Course (1 year), which involves courses aligned with the IT industry requirements
• Master's by Project (2 years), which involves courses aligned with the IT industry needs and also includes a limited research project
• Master's by Thesis (2 years), which requires fewer courses and involves a more substantial research project

The Course-based master's program is not suitable for pursuing higher graduate programs (e.g. PhD). The Project and Thesis master's programs prepare students for higher graduate programs (e.g. PhD) and may provide them with further industrial experience through available Co-op placement opportunities.

Specialization in Artificial Intelligence

The Department of Computer Science is offering a two-year, thesis-based Master of Science in Computer Science (MSc) program with a specialization in Artificial Intelligence (AI).

Students will develop the skills and knowledge to conduct research in the field of Computer Science with a focus on core AI techniques. Upon completion, students will be able to apply and select appropriate AI algorithms and techniques in a variety of industrial sectors and further advance the AI-related research. Topics will include deep learning, natural language processing, machine learning, image processing, pattern recognition, and other emerging technologies. Finally, students will develop research and application-based ethical awareness.

Please note: The AI Specialization is not eligible for the Co-operative Option.

MSc Computer Science Co-operative Program Option - For Project and Thesis based students, only:

A graduate student will normally be admitted to the co-operative program option after completion of two terms, for a starting date in May. Students are expected to obtain an aggregate of 80% or more and must have taken at least 4 half credit courses (excluding non-credit courses, project and thesis).

Co-op employment for 8 months (two terms) must be successfully completed to  satisfy the co-op requirement for the degree. 

Students interested in a co-op placement should inform the Department's Co-op Advisor at least four months in advance of the proposed date of the placement (e.g., by late December for placements beginning in May). The Department's decision as to the suitability of each candidate will be based primarily on academic performance. Successful candidates will work with the Student Success Centre and the university Co-op Coordinator in their search for suitable employment.

Upon completion of the co-op placement, the student will either complete a thesis (Thesis Program option) or complete the Project Program option requirements including the required project course.

NOTE : Students in this program must complete all requirements within six terms (2 years) of continuous registration.   For co-op students, the duration of the co-op placement will be added to the program time limit.

Admission Requirements for Masters

Applicants for admission must be graduates of a recognized university, college, or institute as well as show evidence of scholarly achievement. Except where otherwise stated in the Admission Requirements of a particular program, degree students must have a four year bachelor's degree or its equivalent with at least second class standing (B) based on their last 20 half courses or equivalent.

For applicants from countries that follow a British-patterned grading system, please note:

• Overall standings are normally reported in lieu of an average. The CGPA can be determined on the basis of annual or overall standings as reported on the transcript or degree certificate.
• A minimum grade of B, or Second Class, Upper Division, is required.
• The National Diploma and Higher National Diploma are not recognized for admission to a graduate-level program.
• Be sure to include a copy of your institution grading scale when uploading your transcripts.
• If in doubt, you may wish to order a WES International Credential Advantage (iCap) report from wes.org

An applicant holding a degree other than one in the discipline area to which admission is sought will be considered on the basis of courses taken and academic standing. A Qualifying Year at the undergraduate level may be required to meet the admission standards. Courses taken as part of a Qualifying Year can not be used as credit towards a graduate degree.

Meeting the minimum requirements does not necessarily guarantee admission. No candidate will be admitted unless the academic unit recommends admission. All applicants will be advised by the Office of Graduate Studies in writing of their admission status.

• View English Language Proficiency Requirements
• View Lakehead University Calendar Disclaimer

Program Specific Requirements

In addition to the general admission requirements for Master programs, the following minimum requirements also apply :

• A student entering the Master's program is expected to have at least a "B" average in an Honours Computer Science program or equivalent from an accredited university and the necessary undergraduate prerequisites for the graduate courses to be completed.
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Academic Fees and Important Payment Information

• General Information about University Fees
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• Student Fee and Payment Information
• Refund Schedule

Graduate Funding

At Lakehead University, we realize the importance of financial support for graduate students.

Therefore, financial assistance opportunities are available in several forms and are generally awarded to students by individual programs on the basis of academic promise and financial need.

The different funding options available include:

• Graduate Scholarships, Bursaries, and Awards
• Graduate Assistantships
• Faculty Research Scholarships

For your convenience, a searchable database of graduate scholarships, bursaries, and awards is provided below . Award eligibility, criteria, and application procedures for graduate funding is indicated for each award. Please use the general search tool to find available funding by program. Alternatively, you may also click the advanced search link to specify available funding by program level, award category and/or award amount.

Although financial support cannot be guaranteed to all graduate students in all programs, we encourage you to inquire about financial assistance with your Graduate Coordinator in your program of study . You may also contact the Graduate Funding Officer in the Faculty of Graduate Studies to learn more about your graduate funding options.

Conditions of Graduate Awards

Graduate scholarships are based on academic merit. Graduate bursaries are based on financial need, although there may be a merit component to the bursary. Where the award designates that an application is required, only those students who have submitted the specified application by the deadline will be considered for those awards. Late and/or incomplete applications will not be considered. Only successful applicants will be notified.

Recipients of scholarships, awards and bursaries must be registered in order to receive funding. Graduate awards are applied to any outstanding balance on the student's account. Students are entitled to their awards only after their fees are paid in full. Only students with credit account balances will be refunded the balance of the overpayment. Overpayment refunds of these awards will be issued at the end of September, January and May each year.

The University reserves the right to make changes without prior notice to the terms, conditions and award values listed in this section and in the University Calendar.

The most up-to-date internal awards and applications are on our new award system MyAwards

Graduate Studies Funding Database

Required application documents.

Applicants for admission must be graduates of an accredited university, college, or institute as well as show evidence of scholarly achievement. Except where otherwise stated in the admission requirements of a particular program, domestic degree students must have a four year bachelor's degree or its equivalent with at least (B) based on their last 20 half courses or equivalent. We recommend that International applicants have an overall standing of Second Class - Upper Division or higher.

Meeting the minimum application requirements does not guarantee admission. The Faculty of Graduate Studies will advise all applicants in writing of admission decisions once they are received from the program. Applicants are encouraged to regularly monitor their Lakehead University email and application portal for the most current information.

The first step in the application process is to complete the online graduate studies application form.

After you have submitted the online form along with the required $125 CAD application fee, you will be provided with an online account where you can complete the remaining steps of the application process which include uploading the required supporting documents and monitoring the status of your application.

Click here to Apply to Graduate Studies

After you have applied 

After you have submitted the online application form, you can access your account here . Any change in your application status will be reflected in this portal.

• An electronic reference form will be automatically sent by email to the references you identify on the graduate studies application form
• This form is requested in support of the applicant's ability to undertake advanced study and research
• Click here for information about transcript requirements
• Click here for information about proof of degree requirements
• For a list of program specific documents, please see this program's Additional Application Information section (if required, see above)
• For information about English test results, please see our Academic Calendar

Additional Application Information

Please do not send in your official transcript(s) or proof of degree as these items will be discarded. If you are recommended for admission we will request the documents at that time.

You will need to provide your unofficial documents: final transcript, proof of graduation, CV, Statement of Purpose, proof of English language, three references, and the Computer Science Background Form.

Use the following form to provide a background of your Computer Science experience. Please ensure that you read and follow the instructions on how to fill out the Computer Science Background Form, below. You must submit the Computer Science Background Form with your application, in order to be considered for admission. 

• Instructions on how to complete Computer Science Background Form
• Computer Science Background Form (xlsx)

Registration Procedures

Check to make sure all of your course selections are currently being offered by referring to the University Course Calendar and the University Course Time Tables .

• View Registration Regulations
• View Graduate Course Time Tables
• View How & Where to Register for Courses
• Check Your Eligibility to Register  You should register as soon as you are eligible
• Review the Academic Schedule of Dates for registration deadlines & important dates

University Graduate Studies & General Regulations & Policies

• View University and Graduate Study Regulations, Policies and Guidelines

Application Availability

Fall 2024 (September)

International Application Deadline - March 1st

Domestic Applications are still being accepted.

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