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 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:
- computer applications in a particular field (e.g. communications,
energy systems)
- algorithms and methodologies for solution of complex problems
by computer (e.g. graph theory, operations research, optimization,
simulation and modelling)
- computer methods and technologies (e.g. databases, software
engineering, computer languages)
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 1.5 credit courses in place of
the thesis, 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 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 yearsand
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
- 70.589 Combinatorial Optimization
- 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
- 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: Array
Signal Processing with Applications to Acoustics
- 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 course 95.484 Design and Analysis of Algorithms due to
overlap of course material with 93.582.