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.
K3(Lec: 3, Lab: 0, Tut: 0)

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. Applications in various areas.
(Lec: 3, Lab: 1, Tut: 0)

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.
(Lec: 3, Lab: 0, Tut: 0)

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 biclustering; attribute selection.
K3(Lec: 3, Lab: 0, Tut: 0)

Introduction to scientific computing: floating point arithmetic, algorithm design, error analysis, ill-conditioning. Zero-finding. Linear equations. Interpolation. Integration. Least-squares fitting. Effective use of library programs, with discussion of their limitations and some aspects of their design and implementation.
COURSE DELETED 2019-2020
(Lec: 3, Lab: 0, Tut: 0)

Introduction to management of small and medium-scale software projects. Advanced programming methodology using the programming language C++. Includes a significant programming project.
(Lec: 3, Lab: 0, Tut: 1)

Abstractions and patterns of interactions and relationships among modules. Design recovery; relationship of architecture to requirements and testing.
K4(Lec: 3, Lab: 0, Tut: 1)

This course provides an applied introduction to the principles and practice of the engineering of software artifacts. Topics include: processes for managing software development, software architecture, software design, software quality management, software testing and human-factors of computing systems. The course is illustrated with case studies in industrial practice in software engineering. (0/0/0/34/8)~ COURSE DELETED IN 2009/10 ~

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.
(Lec: 3, Lab: 0, Tut: 0)

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. Alternately offered as CISC 325.
(Lec: 3, Lab: 0, Tut: 0)

An introduction to software architectural design through the application domain of game development. Topics will include notations for expressing static and dynamic aspects of software architecture, design patterns, interface design, and application of these techniques to 3D games, mobile games and web-based games.
COURSE DELETED 2017-2018
(Lec: 3, Lab: 0, Tut: 1)

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).
(Lec: 3, Lab: 0, Tut: 0)

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. Enrolment is limited.
(Lec: 3, Lab: 0, Tut: 0)

Data models: relational, entity-relationship. Relational query languages: relational algebra and SQL. Relational database design. Application interfaces and embedded SQL. Storage and indexing.
(Lec: 3, Lab: 0, Tut: 0)

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 biclustering; attribute selection.
COURSE DELETED 2017-2018
(Lec: 3, Lab: 0, Tut: 0)

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.
(Lec: 3, Lab: 0, Tut: 0)

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.
(Lec: 3, Lab: 1, Tut: 0)

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 specification; program specification: abstract models; verification; specification-based validation.
(Lec: 3, Lab: 0, Tut: 0)

Advanced user interface styles such as multimedia, support for collaboration over the Internet, virtual reality and wearable computers. Processes supporting the design of advanced user interfaces. Implementation techniques.
NOT OFFERED 2022-2023
(Lec: 3, Lab: 0, Tut: 0)

Topics include the presentation and storage of data, implementation concerns, and the integration of databases with other areas of computer science.
NOT OFFERED 2022-2023
(Lec: 3, Lab: 0, Tut: 0)

Operating systems for distributed architectures: distributed system characteristics, process synchronization and communication. Basic distributed algorithms. Principles of fault tolerance. Reliable broadcast. Naming. File systems. Load balancing. Layering, Security.
NOT OFFERED 2022-2023
(Lec: 3, Lab: 0, Tut: 0)

Artificial Neural Networks (ANN) and Genetic Algorithms (GA) for problem solving and prediction tasks such as classification, clustering, optimization and data reduction and modeling human cognition, with application to real world problems. Ongoing research in this area in various application domains.
(Lec: 3, Lab: 0, Tut: 0)

An 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.
(Lec: 3, Lab: 0, Tut: 0)

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, and stereo vision.
(Lec: 3, Lab: 0, Tut: 0)

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.
(Lec: 3, Lab: 0, Tut: 1)

Introduction to computational approaches to the problems in molecular biology. This will include the study of areas such as techniques and algorithms for sequence analysis and alignment; molecular databases; protein structure prediction and molecular data mining.
(Lec: 3, Lab: 0, Tut: 0)

Current topics in the application of information technology to medicine, including computed tomography and x-ray imaging: 2D and 3D ultrasound; computer-assisted planning of interventional procedures; image registration; computer-assisted surgery; bioelectric signals; picture archiving and communication systems (PACS).
(Lec: 3, Lab: 0, Tut: 0)