This course introduces the fundamentals of computer graphics and principles of raster image generation. Topics include: graphics primitives, coordinate systems, transformations, rendering techniques, and geometric modelling.

The history, development, and design principles for programming notations. The design and internal operations of the major notational categories are examined in detail. Students are expected to become proficient in at least four languages they have not previously learned, typically chosen from historical, modern working, and cutting edge languages and from among such (non-exclusive) categories as Algol-descended, functional, scripting, Web-based, modular, application-specific, visual, and object oriented.

This course is designed to give students the ability to analyze, formulate, and program problems related to discrete simulation methods. The course introduces students to queuing theory and some commonly used continuous and discrete statistical distributions. By the end of the course, students are able to simulate real world computer systems and industrial manufacturing systems.

This is a second course in the topics of pure mathematics, particularly those most commonly used in the study of computing science and related applications. It includes proof techniques, models of computation, formal languages, analysis of algorithms, trees and advanced general graph theory with applications, finite state and automata theory, encryption, and an elementary introduction to mathematical structures such as groups, rings, and fields.

An introduction to database management systems, overviewing issues related to the design, organization, and management of databases. Topics include logical database design, entity relationship (ER) models, and formal relational query languages such as the Structured Query Language (SQL).

Operating system and control software at a low level, memory management, processor management, storage management, and system architecture are among the topics considered.

This course covers numerical techniques for solving problems in applied mathematics, including error analysis, roots of equations, interpolation, numerical differentiation and integration, ordinary differential equations, matrix methods and selected topics from among: eigenvalues, approximation theory, non-linear systems, boundary-value problems, numerical solution of partial differential equations.

This course looks at network protocols, network operating systems, and the construction and maintenance of server sites.

Symbolic and numerical computations used in scientific modelling based on Calculus and Linear Algebra, with emphasis on applications in physics and biology. Topics include error analysis, linear systems, roots of equations, interpolation, numerical differentiation, and integration. Further topics may include: eigenvalues and singular values, approximation theory, and non-linear systems.

Focuses on specialized areas in computing to build depth and strengthen technical competence beyond the fundamentals. Students learn established approaches and apply them effectively to well-defined problems. Topics and pre-requisites vary by offering and reflect current trends and faculty expertise.