Information and Systems Science Committee

See the Department of Mathematics and Statistics; Department of Systems and Computer Engineering; or the School of Computer Science

The Committee

Chair of the Committee:
M.J. Moore

The program of graduate study and research leading to the degree of Master of Science in Information and Systems Science is offered by the Committee with the cooperation of the Department of Systems and Computer Engineering, the Department of Mathematics and Statistics, and the School of Computer Science.

The purpose of the program is to provide training in the use and application of computers, to those who have not studied extensively in this field at the undergraduate level. The process of using the computer in problem-solving is stressed. The program is flexible, though individual concentrations are usually in one of three broad areas:

Close links are maintained with the scientific, industrial, and technological communities, and an effort is made to direct students to project work of current practical significance.

Qualifying-Year Program

Applicants who have a general (pass) bachelor’s degree, or who otherwise lack the required undergraduate preparation, may be admitted to a qualifying-year program. Refer to the General Regulations section of this Calendar for regulations governing the qualifying year.

Master of Science

Admission Requirements

Applicants should have an honours bachelor’s degree, or equivalent, with at least high honours standing, in mathematics, engineering, physics, chemistry, computer science, operations research, experimental psychology, econometrics, management science, or a related discipline. Undergraduate preparation should include at least two full courses in computing and a minimum of three full courses in mathematics, at least one of which is at the third-year level or higher. In addition, the student is required to have some knowledge of quantitative applications, such as numerical analysis, simulation, operations research, etc.

Admissions to the program will be made through one of the three participating departments. Since space and laboratory facilities will be provided by one of the departments, students should apply through the department with which they wish to be most closely associated.

Program Requirements

The normal program comprises 4.0 credits (or the equivalent) and a 1.5 credit thesis; additional requirements may also be stipulated, depending upon the individual student’s background. With the approval of the Committee, students who have substantial work experience may be permitted to substitute, in place of the thesis, 1.5 credit courses, one of which must be a graduate project course.

Students must take at least 1.0 credit (or the equivalent) from the department in which they are registered, and at least 0.5 credit from each of the other two participating departments. Students must also take course Information and Systems Science 93.582: Introduction to Information and Systems Science.

Each student should consult with his/her faculty adviser in the selection of a course pattern related to his/her principal area of interest.

Each candidate submitting a thesis will be required to undertake an oral examination on the subject of his/her thesis.

Course work may be completed on either a full-time or part-time basis. Thesis research normally requires full-time residence at the University; however, a candidate may be permitted to carry out thesis work off campus provided that suitable arrangements are made for supervision and experimental work, and prior approval is given by the Committee.

Guidelines for Completion of Master’s Degree

Full-time students in the M.Sc. in Information and Systems Science will normally complete the degree requirements in two years and part-time students within four years. In order to meet this goal, full-time students should arrange a thesis supervisor within the first term of study, and should try to complete the course requirements as quickly as possible.

Graduate Courses

  • Information and Systems Science 93.582F1
    Introduction to Information and Systems Science
    An introduction to the process of applying computers in problem solving. Emphasis is placed on the design and analysis of efficient computer algorithms for large, complex problems. Applications in a number of areas are presented: data manipulation, databases, computer networks, queuing systems, optimization.
    (Also listed as Mathematics 70.582, Engineering 94.582, Computer Science 95.582)

  • Information and Systems Science 93.598F3, W3, S3
    M.Sc. Thesis in Information and Systems Science (Also listed as Mathematics 70.598, Engineering 94.598, Computer Science 95.598)

    Department of Mathematics and Statistics

    Undergraduate Courses

    70.301 Real Analysis

    70.302 Advanced Calculus

    70.310 Modern Algebra

    70.350 Mathematical Statistics

    70.403 Functional Analysis

    70.451 Probability Theory

    70.452 Survey Sampling

    70.453 Applied Multivariate Analysis

    70.456 Non-Parametric Methods

    70.457 Statistical Inference

    70.458 Stochastic Models

    70.459 Topics in Stochastic Optimization and Advanced Mathematical Modelling

    70.470 Partial Differential Equations

    70.471 Topics in Partial Differential Equations

    70.473 Qualitative Theory of Ordinary Differential Equations

    70.481 Topics in Combinatorics

    70.482 Introduction to Mathematical Logic

    70.483 Computable Functions

    70.485 Theory of Automata

    70.486 Numerical Linear Algebra

    70.487 Game Theory

    70.488 Graph Theory and Algorithms

    70.496 Directed Studies

    Graduate Courses

    70.507 Real Analysis I (Measure Theory and Integration)

    70.508 Real Analysis II (Functional Analysis)

    70.517 Algebra I

    70.519 Algebra II

    70.552 Sampling Theory and Methods

    70.553 Linear Models

    70.554 Stochastic Processes and Time Series Analysis

    70.555 Design of Experiments

    70.556 Robust Statistical Inference

    70.557 Advanced Statistical Inference

    70.558 Topics in Stochastic Processes

    70.559 Multivariate Analysis

    70.561 Stochastic Optimization

    70.565 Theory of Automata

    70.567 Game Theory

    70.569 Topics in Combinatorial Mathematics

    70.571 Stochastic Models

    70.581 Linear Optimization

    70.583 Nonlinear Optimization

    70.584 Topics in Operations Research

    70.585 Topics in Algorithm Design

    70.586 Numerical Analysis

    70/95.587 Formal Language and Syntax Analysis
    70.588 Combinatorial Optimization I

    70.589 Combinatorial Optimization II

    70.590 Seminar

    70.591 Directed Studies

    70.593 Project

    Department of Systems and Computer Engineering

    Undergraduate Courses

    94.303 Introduction to Real-Time Systems

    94.310 Systems Analysis

    94.333 Real-Time Concurrent Systems

    94.351 Communication Theory

    94.361 Microprocessor Systems

    94.401 Operating Systems

    94.405 Discrete Simulation and its Applications

    94.445 Discrete Time Systems

    94.457 Architecture of Computer Systems

    94.460 Digital Communications

    Frame 1
    94.462 Introduction to Computer Communications

    94.480 Software Engineering

    94.481 Software Engineering Project

    94.485 Computer Systems Design Laboratory

    Graduate Courses

    94.501 Simulation and Modelling

    94.504 Mathematical Programing for Engineering Applications

    94.505 Optimization Theory and Methods

    94/95.507 Expert Systems
    94.511 Design of High Performance Software

    94.517 Queuing Systems

    94.518 Topics in Information Systems

    94.519 Teletraffic Engineering

    94.521 Computer Communication

    94.527 Distributed Processing Systems

    94.531 System Design with Ada



    94.535 Representations, Methods and Tools for Concurrent Systems

    94.538 Computer Architecture and Parallel Processing


    94.541 Adaptive Control

    94.542 Advanced Dynamics with Applications to Robotics

    94.552 Advanced Linear Systems

    94.553 Stochastic Processes

    94.554 Principles of Digital Communication


    94.558 Digital Systems Architecture

    94.560 Adaptive Signal Processing

    94.561 Neural Signal Processing

    94.562 Digital Signal Processing

    94.563 Digital Signal Processing: Microprocessors, Software and Applications

    94.564 Advanced Topics in Digital Signal Processing

    94.565 Advanced Digital Communication

    94.566 Introduction to Mobile Communications

    94.567 Source Coding and Data Compression

    94.568 Wireless Communication Systems Engineering

    94.569 Digital Television

    94.571 Operating System Methods for Real-time Applications

    94.573 Integrated Database Systems

    94.574 Elements of Computer Systems

    94.576 Analytical Performance Models of Computer Systems

    94.577 Teleprocessing Software Design

    94.579 Advanced Topics in Software Engineering


    94.581 Advanced Topics in Computer Communications

    94.583 Logic Programing

    94.584 Advanced Topics in Communications Systems



    94.596 Directed Studies

    School of Computer Science

    Undergraduate Courses

    95.300 Operating Systems

    95.304 Software Systems Design

    95.305 Database Management Systems

    95.401 Concurrent Programing

    95.402 Computer Graphics

    95.403 Transaction Processing Systems

    95.405 A First Course in Robotics and Computer Vision

    95.407 Applied Artificial Intelligence

    95.408 Performance Modelling

    95.409 Introduction to Parallel and Systolic Computing

    Graduate Courses

    95.501 Foundations of Programing Languages

    95.502 User Interface Facilities

    95.503 Principles of Distributed Computing

    95.504 Topics in Arithmetic Complexity

    95.505 Learning Systems for Random Environments

    95.506 Natural Language Understanding

    94/95.507 Expert Systems
    95.508 Computational Geometry

    95.509 Associative Data Structures and Advanced Databases

    95.510 Topics in Artificial Intelligence

    95.511 Distributed Databases and Transaction Processing Systems

    95.512 Distributed Operating Systems

    95.513 Cryptography

    95.514 Object-Oriented Systems

    95.515 Parallel Processing Systems

    95.516 Languages for Parallel Computing

    95.520 Cerebral Computations

    95.522 Network Reliability

    95.524 Computational Aspects of Geographic Information Systems

    95.526 Genetic Algorithms and Artificial Life

    95.528 Complexity of Boolean Functions

    95.573 Algorithm Analysis and Design

    95.574 Parallel Algorithms and their VLSI Implementation
    Due to the interdisciplinary nature of ISS, a student will in some cases benefit by taking an undergraduate course at the 300 or 400 level as part of his/her program. Where a 300 level course is to be taken, it

    will be extra to the degree requirements, or else arrangements will be made to enrich the subject matter, normally through a directed study course with the professor. Students may include 1.0 credit (or the equivalent) at the 400 level in their program without penalty, with the approval of the Department. The 300 and 400 level courses listed here are those most likely to interest ISS students; see the Undergraduate Calendar for a complete list. Students in the program are prohibited from taking Computer Science 95.484 Design and Analysis of Algorithms due to overlap of course material with Information and Systems Science 93.582.