Academic Calendar 2022-2023

Computing and Information Science (CISC)

CISC 101  Elements of Computing Science  Units: 3.00  

Introduction to algorithms: their definition, design, coding, and execution on computers. Intended for students who have no programming experience. All or most assignment work will be completed during lab time.
NOTE Also offered online. Consult Arts and Science Online. Learning Hours may vary.
NOTE Sufficient preparation for CISC 121; alternative to CISC 110 and CISC 151.
LEARNING HOURS 120(36L;84P).

Requirements: Prerequisite None. Exclusion APSC 142; APSC 143; CISC 110; CISC 151. One-Way Exclusion May not be taken with or after CISC 121; CISC/CMPE/COCA/COGS/SOFT at the 200-level or above. Note This course is intended for students who have no programming experience.  
Offering Faculty: Faculty of Arts and Science  
CISC 102  Discrete Mathematics for Computing l  Units: 3.00  

Introduction to mathematical discourse and proof methods. Sets, functions, sequences, and relations. Properties of the integers. Induction. Equivalence relations. Linear and partial orderings.
NOTE Also offered online. Consult Arts and Science Online. Learning Hours may vary.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite None. One-Way Exclusion May not be taken with or after CISC 203.  
Offering Faculty: Faculty of Arts and Science  
CISC 110  Creative Computing  Units: 3.00  

Introduction to fundamental programming concepts in the context of visual, interactive media. Students may develop applications in any domain (e.g., fine art, education, commerce, physical or social sciences) while learning about algorithms, program design, logic, program control flow, functions, testing, etc.
NOTE Sufficient preparation for CISC 121; alternative to CISC 101 and CISC 151.
NOTE With permission of the School, students with programming experience may take this concurrently with CISC 121.
LEARNING HOURS 120 (36L;84P).

Requirements: Prerequisite None. Exclusion APSC 142; APSC 143; CISC 101; CISC 151. One-Way Exclusion May not be taken with or after CISC 121; CISC/CMPE/COCA/COGS/SOFT at the 200-level or above. Note No computing or art background required.  
Offering Faculty: Faculty of Arts and Science  
CISC 121  Introduction to Computing Science I  Units: 3.00  

Introduction to design, analysis, and implementation of algorithms. Recursion, backtracking, and exits. Sequences. Elementary searching and sorting. Order-of-magnitude complexity. Documentation, iterative program development, translating natural language to code, testing and debugging.
NOTE Also offered online. Consult Arts and Science Online. Learning Hours may vary.
LEARNING HOURS 120 (36L;84P).

Requirements: Prerequisite None. Corequisite (CISC 102 or MATH 110 or MATH 111 or MATH 112 or MATH 120 or MATH 121 or MATH 123 or MATH 124 or MATH 126 or APSC 171 or APSC 172 or APSC 174 or COMM 161 or COMM 162). Exclusion APSC 143. Recommended Some programming experience (such as high-school level programming or CISC 101 or CISC 110 or CISC 151).  
Offering Faculty: Faculty of Arts and Science  
CISC 124  Introduction to Computing Science II  Units: 3.00  

Introduction to object-oriented design, architecture, and programming. Use of packages, class libraries, and interfaces. Encapsulation and representational abstraction. Inheritance. Polymorphic programming. Exception handling. Iterators. Introduction to a class design notation. Numerical computation. Applications in various areas.
LEARNING HOURS 120 (36L;24Lb;60P)

Requirements: Prerequisite A minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 121. Corequisite (CISC 102 or MATH 110 or MATH 111 or MATH 112 or MATH 120 or MATH 121 or MATH 123 or MATH 124 or MATH 126 or APSC 171 or APSC 172 or APSC 174 or COMM 161 or COMM 162).  
Offering Faculty: Faculty of Arts and Science  
CISC 151  Elements of Computing with Data Analytics  Units: 3.00  

Introduction to algorithms: their definition, design, coding, and execution on computers, with applications drawn from data analytics, including simple prediction and clustering. Intended for students who have no programming experience. All or most assignment work will be completed during lab time.
NOTE Sufficient preparation for CISC 121; alternative to CISC 101 and CISC 110.
LEARNING HOURS 120 (36L;84P).

Requirements: Prerequisite None. Exclusion APSC 142; APSC 143; CISC 101; CISC 110. One-Way Exclusion May not be taken with or after CISC 121; CISC/CMPE/COCA/COGS/SOFT at the 200-level or above.  
Offering Faculty: Faculty of Arts and Science  
CISC 181  Digital Societies  Units: 3.00  

This introductory course provides a broad overview and ethical implications of technological topics and trends in the digital world such as the Internet of Things (IoT), Social Networks, Security and Privacy, Data Analytics, and Artificial Intelligence (AI). No programming experience is required.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite None. Equivalency CISC P81.  
Offering Faculty: Faculty of Arts and Science  
CISC 203  Discrete Mathematics for Computing II  Units: 3.00  

Proof methods. Combinatorics: permutations and combinations, discrete probability, recurrence relations. Graphs and trees. Boolean and abstract algebra.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Level 2 or above and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 121 and [CISC 102 or MATH 110]).  
Offering Faculty: Faculty of Arts and Science  
CISC 204  Logic for Computing Science  Units: 3.00  

Elements of mathematical logic with computing applications. Formal proof systems for propositional and predicate logic. Interpretations, validity, and satisfiability. Introduction to soundness, completeness and decidability.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Level 2 or above and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 121 and [CISC 102 or MATH 110]).  
Offering Faculty: Faculty of Arts and Science  
CISC 220  System Level Programming  Units: 3.00  

Basic concepts of Unix-like systems. Shells and scripting. System-level programming in the C language. Software development tools and techniques.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Level 2 or above and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 121. Corequisite CISC 124.  
Offering Faculty: Faculty of Arts and Science  
CISC 221  Computer Architecture  Units: 3.00  

The descriptive levels of computer architecture. Instruction-set architectures. Assembly Language. Data representation. Support for operating-system management and high-level languages. Input/output and interrupts. Designing for performance. Digital Logic.
LEARNING HOURS 120 (12L;24G;84P)
RECOMMENDATION CISC 220/3.0.

Requirements: Prerequisite Level 2 or above and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 124. Recommended CISC 220.  
Offering Faculty: Faculty of Arts and Science  
CISC 223  Software Specifications  Units: 3.00  

Introduction to techniques for specifying the behaviour of software, with applications of these techniques to design, verification and construction of software. Logic-based techniques such as loop invariants and class invariants. Automata and grammar-based techniques, with applications to scanners, parsers, user-interface dialogs and embedded systems. Computability issues in software specifications.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Level 2 or above and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 124 and CISC 204).  
Offering Faculty: Faculty of Arts and Science  
CISC 226  Game Design  Units: 3.00  

An introduction to techniques for designing elementary computer games. Topics will include game development tools and processes, principles of game design, game prototyping and game evaluation.
LEARNING HOURS 120 (36L;60G;24P)

Requirements: Prerequisite Level 2 or above and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 124.  
Offering Faculty: Faculty of Arts and Science  
CISC 235  Data Structures  Units: 3.00  

Design and implementation of advanced data structures and related algorithms, including correctness and complexity analysis.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Level 2 or above and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 124 and CISC 203).  
Offering Faculty: Faculty of Arts and Science  
CISC 251  Data Analytics  Units: 3.00  

Introduction to data analytics; data preparation; assessing performance; prediction methods such as decision trees, random forests, support vector machines, neural networks and rules; ensemble methods such as bagging and boosting; clustering techniques such as expectation-maximization, matrix decompositions, and bi-clustering; attribute selection.
LEARNING HOURS 120 (36L;24Lb;60P).

Requirements: Prerequisite A cumulative GPA of a 1.70 or higher. Exclusion CISC 333; CMPE 333. Recommended Experience with problem solving in any discipline.  
Offering Faculty: Faculty of Arts and Science  
CISC 271  Linear Data Analysis  Units: 3.00  

Elements of linear algebra for data analysis, including: solution of linear equations; vector spaces; matrix decompositions; principal components analysis; linear regression; hyperplane classification of vectorial data.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Level 2 or above and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in {[CISC 101 or CISC 110 or CISC 151 or CISC 121] and [MATH 110 or MATH 111 or MATH 112] and [MATH 120 or MATH 121 or (MATH 123 and MATH 124) or MATH 126]}. Exclusion MATH 272.  
Offering Faculty: Faculty of Arts and Science  
CISC 282  Fundamentals of Web Development  Units: 3.00  

This course surveys current best practices for implementing attractive, usable, secure and maintainable web applications. Other issues considered include: accessibility, platform and browser independence, licensing of intellectual property, scalability, user privacy, and using web technologies in mobile development.
LEARNING HOURS 120 (36L;48O;36P)

Requirements: Prerequisite Level 2 or above and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 124. Equivalency CISC P82.  
Course Equivalencies: cisc282; ciscP82  
Offering Faculty: Faculty of Arts and Science  
CISC 320  Fundamentals of Software Development  Units: 3.00  

Introduction to management of small and medium-scale software projects. Advanced programming methodology using the programming language C++. Includes a significant programming project.
LEARNING HOURS 120 (36L;24T;24G;36P).

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 235.  
Offering Faculty: Faculty of Arts and Science  
CISC 322  Software Architecture  Units: 3.00  

Abstractions and patterns of interactions and relationships among modules. Design recovery; relationship of architecture to requirements and testing.
LEARNING HOURS 120 (36L;24T;36G;24P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 223 and CISC 235). Exclusion CISC 326.  
Offering Faculty: Faculty of Arts and Science  
CISC 324  Operating Systems  Units: 3.00  

Layered operating systems for conventional shared memory computers: concurrent processes. Synchronization and communication. Concurrent algorithms. Scheduling. Deadlock. Memory management. Protection. File systems. Device management. Typical layers.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 221 and CISC 235).  
Offering Faculty: Faculty of Arts and Science  
CISC 325  Human-Computer Interaction  Units: 3.00  

Developing usable software requires that human factors be considered throughout the design and development process. This course introduces a series of techniques for development and evaluating usable software, and shows how these techniques can be integrated into a process for software development.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite C- (or P in Winter 2020) in (CISC124 and CISC235) and registration in a School of Computing Plan. Exclusion SOFT325  
Offering Faculty: Faculty of Arts and Science  
CISC 326  Game Architecture  Units: 3.00  

An introduction to software architectural design through the application domain of game development. Abstractions and patterns of interactions and relationships among modules. Design recovery. Relationship to requirements and testing
LEARNING HOURS 120 (36L;24T;24G;36P).

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 223 and CISC 235). Exclusion CISC 322. Recommended CISC 226.  
Offering Faculty: Faculty of Arts and Science  
CISC 327  Software Quality Assurance  Units: 3.00  

Validation of software throughout the life cycle. Comparative effectiveness in defect removal of formal methods (proofs of correctness), inspection (walkthroughs and reviews), and testing (unit, integration, and system testing; white box versus black box).
LEARNING HOURS 120 (36L;84G)

Requirements: Prerequisite C- (or P in Winter 2020) in (CISC 220 and CISC 124) and registration in a School of Computing Plan. Exclusion SOFT 327  
Offering Faculty: Faculty of Arts and Science  
CISC 330  Computer-Integrated Surgery  Units: 3.00  

Concepts of computer-integrated surgery systems and underlying techniques such as medical-image computing, robotics, and virtual reality, learned through real-life applications and problems. Techniques learned in class will be applied in a hands-on surgery session where students perform minimally invasive surgery with virtual-reality navigation tools.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 121 and CISC 271). Exclusion COMP 329; COMP 230. Equivalency COMP 230.  
Course Equivalencies: CISC330; COMP230  
Offering Faculty: Faculty of Arts and Science  
CISC 332  Database Management Systems  Units: 3.00  

Data models: relational, entity-relationship. Relational query languages: relational algebra and SQL. Relational database design. Application interfaces and embedded SQL. Storage and indexing.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Level 2 or above and registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 102 and CISC 124). Exclusion COMM 392.  
Offering Faculty: Faculty of Arts and Science  
CISC 335  Computer Networks  Units: 3.00  

Fundamental concepts in the design and implementation of computer communication networks, protocols, and applications. Overview of network architectures; applications; network programming interfaces (e.g., sockets); transport; congestion; routing and data link protocols; addressing; local area networks; wireless networks, mobility management; security.
LEARNING HOURS 120 (36L;84P).

Requirements: Prerequisite Registration in a School of Computing Plan and a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 324.  
Offering Faculty: Faculty of Arts and Science  
CISC 340  Digital Systems  Units: 3.00  

Combinational circuits; sequential circuits; digital systems design; micro-programming; bus structures; data communications; interface design; microprocessor systems.
LEARNING HOURS 120 (12L;24G;84P)

Requirements: ASC Students: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 221. Exclusion None. FEAS Students: Exclusion ELEC 272; ELEC 373.  
Offering Faculty: Faculty of Arts and Science  
CISC 351  Advanced Data Analytics  Units: 3.00  

Design and implementation of complex analytics techniques; predictive algorithms at scale; deep learning; clustering at scale; advanced matrix decompositions, analytics in the Web, collaborative filtering; social network analysis; applications in specialized domains.
LEARNING HOURS 120 (36I;36Lb;84P)

Requirements: Prerequisite A minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 251 and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (3 units in STAT or 3 units from STAT_Options). Exclusion CISC 371; CISC 372.  
Offering Faculty: Faculty of Arts and Science  
CISC 352  Artificial Intelligence  Units: 3.00  

An introduction to the basic principles and tools of artificial intelligence. Problem solving methods and knowledge representation techniques.
LEARNING HOURS 120 (36L;84P)
RECOMMENDATION CISC 360/3.0 or CISC 260/3.0.

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 235. Recommended CISC 360 or CISC 260.  
Offering Faculty: Faculty of Arts and Science  
CISC 360  Programming Paradigms  Units: 3.00  

Review of imperatives programming features. Introduction to other widely used programming paradigms. Functional programming languages, such as LISP and Haskell. Higher order functions, lazy evaluation, abstract and recursive types, structural induction, symbolic expressions. Logic programming languages, such as PROLOG. Operational interpretation of predicates and terms, proof search, unification, backtracking. Typical applications.
LEARNING HOURS 120 (36L;84P)
EQUIVALENCY CISC 260/3.0.

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 124 and CISC 204). Equivalency CISC 260.  
Offering Faculty: Faculty of Arts and Science  
CISC 365  Algorithms I  Units: 3.00  

Principles of design, analysis and implementation of efficient algorithms. Case studies from a variety of areas illustrate divide and conquer methods, the greedy approach, branch and bound algorithms and dynamic programming.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 203 and CISC 204 and CISC 235).  
Offering Faculty: Faculty of Arts and Science  
CISC 371  Nonlinear Data Analysis  Units: 3.00  

Methods for nonlinear data analysis, particularly using numerical optimization. Applications may include: unconstrained data optimization; linear equality constraints; constrained data regression; constrained data classification; evaluating the effectiveness of analysis methods.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 271 and [STAT 263 or STAT_Options]). Exclusion CISC 351.  
Offering Faculty: Faculty of Arts and Science  
CISC 372  Advanced Data Analytics  Units: 3.00  

Inductive modelling of data, especially counting models; ensemble approaches to modelling; maximum likelihood and density-based approaches to clustering, visualization. Applications to non-numeric datasets such as natural language, social networks, Internet search, recommender systems. Introduction to deep learning. Ethics of data analytics.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 271 and [3.0 units in STAT or STAT_Options]).  
Offering Faculty: Faculty of Arts and Science  
CISC 422  Formal Methods in Software Engineering  Units: 3.00  

Mathematical methods for describing software behaviour and structure. Topics include (but are not limited to) the following: Requirements specification. Module specification: axiomatic, algebraic, and trace specifications. Abstract models. Verification. Specification-based validation.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 223.  
Offering Faculty: Faculty of Arts and Science  
CISC 423  Software Requirements  Units: 3.00  

An integrated approach to discovering and documenting software requirements. Identification of stakeholders; customer, operator, analyst, and developer perspectives. Requirements elicitation. Transition from initial (informal) requirements to semi-formal and formal representations. Requirements analysis process; analysis patterns. Requirements specification techniques. Relation to architecture and user interface design; traceability of requirements.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 223 and CISC 235). Corequisite (CISC 325 and [CISC 322 or CISC 326]).  
Offering Faculty: Faculty of Arts and Science  
CISC 425  Advanced User Interface Design  Units: 3.00  

Advanced user-interface styles such as eye-tracking input, digital desks, wearable computing, ubiquitous and context-aware computing, and tangible interfaces.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 325 or permission of the School.  
Offering Faculty: Faculty of Arts and Science  
CISC 426  Real-Time Systems  Units: 3.00  

Design and implementation of real-time embedded applications. Specifying timing properties: formal and semi-formal methods; soft real-time versus hard real-time. Design notations; language constructs. Real-time operating systems. Abstract device interfaces.

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 324 and CISC 327).  
Offering Faculty: Faculty of Arts and Science  
CISC 432  Advanced Data Management Systems  Units: 3.00  

Storage and representation of "big data", which are large, complex, structured or unstructured data sets. Provenance, curation, integration, indexing and querying of data.
LEARNING HOURS 120 (36L;84P).

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 235 and CISC 332).  
Offering Faculty: Faculty of Arts and Science  
CISC 434  Distributed Systems  Units: 3.00  

Distributed systems goals, characteristics, and architectures. Processes: models, inter-process communication and coordination. Name services. Consistency and replication. Fault tolerance: design for reliable communication and recovery. Security. Development paradigms based on data types: object, file, and web-based systems.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 324.  
Offering Faculty: Faculty of Arts and Science  
CISC 437  Performance Analysis  Units: 3.00  

Analytic and empirical evaluation of the performance of software systems. Performance modeling. Experimental design and statistical techniques for empirical performance analysis.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 324 and CISC 327).  
Offering Faculty: Faculty of Arts and Science  
CISC 447  Introduction to Cybersecurity  Units: 3.00  

An introduction to cybersecurity covering a wide range of vulnerabilities, attacks, and defense mechanisms in individual computers, networks, the Internet and the Web and applications that use them, and storage and computational clouds. The human side of cybersecurity, and the legal and ethical constraints on both attack and defense.
LEARNING HOURS 120(36L;84P)

Requirements: Prerequisite CISC 324 and CISC 335. Exclusion CISC 490 (Topic Title: Computer Security).  
Offering Faculty: Faculty of Arts and Science  
CISC 448  Software Reliability and Security  Units: 3.00  

Software dependability and other related concepts, software process models and methods for reliable software. Software reliability engineering process, software fault tolerance and run-time monitoring. Software security engineering process, secure software design, program security vulnerabilities and software security testing
LEARNING HOURS 120(36L;84P)

Requirements: Prerequisite CISC 327 or CMPE 327.  
Offering Faculty: Faculty of Arts and Science  
CISC 451  Topics in Data Analytics  Units: 3.00  

Content will vary from year to year; typical areas covered may include: tools for large scale data analytics (Hadoop, Spark), data analytics in the cloud, properties of large scale social networks, applications of data analytics in security.
LEARNING HOURS 120 (36I;36Lb;48P)

Requirements: Prerequisite A minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 333 or CISC 351 or CISC 372).  
Offering Faculty: Faculty of Arts and Science  
CISC 452  Neural and Genetic Computing  Units: 3.00  

Introduction to neural and genetic computing. Topics include associative memory systems, neural optimization strategies, supervised and unsupervised classification networks, genetic algorithms, genetic and evolutionary programming. Applications are examined, and the relation to biologic systems is discussed.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 235. Exclusion COGS 400.  
Offering Faculty: Faculty of Arts and Science  
CISC 453  Topics in Artificial Intelligence  Units: 3.00  

Investigation of selected areas of artificial intelligence research. Possible topics include natural language understanding, computational perception, planning, learning, and neurocomputing.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 352.  
Offering Faculty: Faculty of Arts and Science  
CISC 454  Graphics (A)  Units: 3.00  

Introduction to computer graphics, including a review of current hardware; modelling and transformations in two and three dimensions; visual realism: perspective, hidden surface elimination, and shading; colour models; applications in several fields. James Stewart.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Level 3 or above and registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 235 and [MATH 110 or MATH 111 or MATH 112]).  
Offering Faculty: Faculty of Arts and Science  
CISC 455  Evolutionary Optimization and Learning  Units: 3.00  

Building, applying and studying algorithms based on the Darwinian principles of natural evolution. A creative approach to AI able to create novel solutions. Genetic algorithms, evolution strategies, and genetic programming. Application to optimization and learning problems.
LEARNING HOURS 120 (36L;84P).

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 365 and STAT 263).  
Offering Faculty: Faculty of Arts and Science  
CISC 457  Image Processing and Computer  Units: 3.00  

Introduction to fundamental concepts and applications in image processing and computer vision. Topics include image acquisition, convolution, Discrete Fourier Transform, image enhancement, edge detection, segmentation, image registration, human contrast perception, colour perception and reproduction, stereo vision.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in ([MATH 110 or MATH 111 or MATH 112] and [MATH 120 or MATH 121 or MATH 123 or MATH 124 or MATH 126] and CISC 124).  
Offering Faculty: Faculty of Arts and Science  
CISC 458  Programming Language Processors (S)  Units: 3.00  

Introduction to the systematic construction of a compiler: grammars and languages, scanners, top-down and bottom-up parsing, runtime organization, symbol tables, internal representations; Polish notation, syntax trees, semantic routines, storage allocation, code generation, interpreters.
LEARNING HOURS 120 (36L;36Lb;48G)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 121 and CISC 221 and CISC 223).  
Offering Faculty: Faculty of Arts and Science  
CISC 462  Computability and Complexity  Units: 3.00  

Turing machines and other models of computability such as µ-recursive functions and random-access machines. Undecidability. Recursive and recursively enumerable sets. Church-Turing thesis. Resource-bounded complexity. Complexity comparisons among computational models. Reductions. Complete problems for complexity classes.
LEARNING HOURS 120 (36L;84P)
RECOMMENDATION CISC 365/3.0.

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 223. Recommended CISC 365.  
Offering Faculty: Faculty of Arts and Science  
CISC 465  Semantics of Programming Languages  Units: 3.00  

Specifying syntax and semantics; operational and denotational semantics. Lambda calculi, type systems and logical foundations. Meta-theoretic properties. Semantics of imperative languages.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 204 and CISC 223 and [CISC 360 or CISC 260]).  
Offering Faculty: Faculty of Arts and Science  
CISC 466  Algorithms II  Units: 3.00  

A continuation of CISC 365/3.0. Lower bound theory. Average-case analysis of algorithms. Approximation algorithms. Probabilistic algorithms. Parallel algorithms.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 365.  
Offering Faculty: Faculty of Arts and Science  
CISC 467  Fuzzy Logic  Units: 3.00  

History of fuzzy theory; fundamental concepts of fuzzy theory: sets, relations, and logic operators. Approximate reasoning, fuzzy inference, possibility theory. Separation from probability. Fuzzy control systems. Fuzzy pattern recognition. Advanced topics may include fuzzy expert systems, financial systems, graph theory, optimization.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Level 4 or above and registration in a BCMP or COCA Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 204.  
Offering Faculty: Faculty of Arts and Science  
CISC 468  Cryptography  Units: 3.00  

Fundamentals of cryptographic algorithms: secure pseudorandom number generators, hash functions, symmetric-key cryptography (stream ciphers, block ciphers); public-key cryptography (encryption and decryption, digital signatures, key agreement). Applications of cryptography to secure communication protocols and systems.
LEARNING HOURS 120 (36L;84P).

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 235 and CISC 335).  
Offering Faculty: Faculty of Arts and Science  
CISC 471  Computational Biology  Units: 3.00  

Advanced computational approaches to the problems in molecular biology. Techniques and algorithms for sequence analysis and alignment; molecular databases; protein structure prediction and molecular data mining.
LEARNING HOURS 120 (36L;84P).

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 352 and CISC 365).  
Offering Faculty: Faculty of Arts and Science  
CISC 472  Medical Informatics  Units: 3.00  

Current topics in the application of information technology to medical image computing and its use in image-guided medical interventions.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 330.  
Offering Faculty: Faculty of Arts and Science  
CISC 473  Deep Learning  Units: 3.00  

Design of deep neural networks based on leading-edge algorithms such as Restricted Boltzmann Machines, Recurrent Neural Networks, Convolutional Neural Networks, Long-Short Term Machines. Autoencoding as a clustering technique. Applications to prediction problems in natural language and images.
LEARNING HOURS 120 (36L;84P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 371 or [CISC 271 and CISC 352]).  
Offering Faculty: Faculty of Arts and Science  
CISC 474  Reinforcement Learning  Units: 3.00  

Formal and heuristic approaches to problem-solving, planning, knowledge representation and reasoning, Markov decision processes, dynamic programming, temporal-difference learning, Monte Carlo learning, function approximation, integration of learning and planning. Implementing simple examples of logical reasoning, clustering or classification.
LEARNING HOURS 120 (36L;12G;72P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 352.  
Offering Faculty: Faculty of Arts and Science  
CISC 486  Game Development  Units: 3.00  

An introduction to 'engines' used in networked 3-dimensional games. Topics include game-engine architecture and components providing 3-dimensional rendering, physics simulation, sound, artificial intelligence and networking services.
LEARNING HOURS 120 (36L;15G;69P)

Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 226 and [CISC 322 or CISC 326] and CISC 324 and [MATH 110 or MATH 111 or MATH 112]).  
Offering Faculty: Faculty of Arts and Science  
CISC 490  Topics in Computing Science I  Units: 3.00  

Content varies. Not offered every year.
NOTE Learning Hours will vary.

Requirements: Prerequisite Registration in a School of Computing Plan and permission of the instructor.  
Offering Faculty: Faculty of Arts and Science  
CISC 491  Topics in Computing Science II  Units: 3.00  

Content varies. Not offered every year.
NOTE Learning Hours will vary.

Requirements: Prerequisite Registration in a School of Computing Plan and permission of the instructor.  
Offering Faculty: Faculty of Arts and Science  
CISC 492  Topics in Computing III  Units: 3.00  

Content varies. Not offered every year.
NOTE Learning Hours will vary.

Requirements: Prerequisite Registration in a School of Computing Plan and permission of the instructor.  
Offering Faculty: Faculty of Arts and Science  
CISC 496  Game Development Project  Units: 3.00  

Team-based project involving the development of a game using modern tools and software engineering techniques.
LEARNING HOURS 129 (9L;120G)

Requirements: Prerequisite: Registration in a Computing honours plan and (C- in CISC 486) and 30 units in CISC/SOFT/COGS/COCA and 2.6 GPA in all of CISC/SOFT/COGS/COCA Exclusion CISC 496; CISC 498; CISC 499; COGS 499; CISC 500.  
Offering Faculty: Faculty of Arts and Science  
CISC 497  Social, Ethical and Legal Issues in Computing  Units: 3.00  

A wide range of topics of current importance in computing, including technical issues, professional questions, and moral and ethical decisions. Students make presentations, deliver papers, and engage in discussion.
LEARNING HOURS 120 (12L;24S;84P)

Requirements: Prerequisite Level 4 or above and registration in a COMP Major or Specialization Plan and a cumulative GPA of 1.90 and a (GPA of 2.60 in CISC; COCA; COGS; SOFT) and (30.0 units of CISC; COCA; COGS; SOFT) and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 352 or CISC 365).  
Offering Faculty: Faculty of Arts and Science  
CISC 498  Information Technology Project  Units: 6.00  

Topic selected under the supervision of a faculty member. Emphasis is on the application of software engineering techniques to the development of a substantial software system. Group work, oral presentation, participation in design and code review meetings, and delivery of complete software specification and design are required.
LEARNING HOURS 258 (18S;240G)

Requirements: Prerequisite Level 4 or above and registration in a SODE Specialization Plan and a cumulative GPA of 1.90 and a (GPA of 2.60 in CISC; COCA; COGS; SOFT) and (30.0 units in CISC; COCA; COGS; SOFT) and (a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in [CISC 322 or CISC 326] and [CISC 325 or CISC 327]). Exclusion CISC 496; CISC 499.  
Offering Faculty: Faculty of Arts and Science  
CISC 499  Advanced Undergraduate Project  Units: 3.00  

Topic selected under the supervision of a faculty member. Emphasis may be on the development of a large program, or on more theoretical issues. Independent research, an oral presentation, and a written report are required.
LEARNING HOURS 120 (120P)

Requirements: Prerequisite Level 4 or above and registration in a COMP Major or BMCO or COMA or CSCI Specialization Plan and a cumulative GPA of 1.90 and a (GPA of 2.60 in CISC; COCA; COGS; SOFT) and (30.0 units in CISC; COCA; COGS; SOFT) and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 365. Exclusion CISC 496; CISC 498; COGS 499; CISC 500.  
Offering Faculty: Faculty of Arts and Science  
CISC 500  Undergraduate Thesis  Units: 6.00  

Individual research project under the supervision of a School of Computing faculty member. Evaluation is based on an oral presentation and a written thesis. It is the responsibility of the student to make a research proposal and secure a supervisor prior to enrolling in the course.
LEARNING HOURS 240 (24I;216P)

Requirements: Prerequisite Permission of the School and a minimum cumulative GPA of 3.50 or higher and level 4 or above and registration in a COMP Major or BMCO, COGS, COMA, CSCI, or SODE Specialization Plan. Exclusion CISC 496; CISC 499; COGS 499.  
Offering Faculty: Faculty of Arts and Science  
CISC 594  Independent Study  Units: 3.00  

Offering Faculty: Faculty of Arts and Science  
CISC 595  Independent Study  Units: 6.00  

Offering Faculty: Faculty of Arts and Science  
CISC 596  Independent Study  Units: 12.00  

Offering Faculty: Faculty of Arts and Science