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: Frantisek Fiala 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 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 eight half courses and a thesis having a weight of one and one half full courses; 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 three additional half courses in place of the thesis, one of which must be a graduate project course. Students must take at least two half courses from the department in which they are registered, and at least one half course 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. 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 Computer System Design for Performance 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 94.557 Fundamentals of Discrete Systems 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: Speech Communications and Applications 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 94.585 Logic Programing: Techniques and Applications 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 Automata Models of Learning Systems 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 95.573 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 two half courses 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. ISS students are prohibited from taking course 95.484 Design and Analysis of Algorithms due to overlap of course material with 93.582.