Course Descriptions

An introduction to the basic concepts underlying computer hardware, software, operating systems, networks, applications, and coding, for students with little or no previous experience. Students also explore some of the social and ethical implications arising from the pervasive use of digital information technologies. The goals of this course are to gain a broad understanding of the science of computing, to develop practical skills applied to the use of the Internet and common computer applications, and to become actively engaged with both the promise and challenges of digital technology.

An introduction to the basic concepts of hardware, software, and computer programming using Sparki robots, for students with little or no experience. Students learn to apply fundamental engineering design and programming principles, and are exposed to a variety of topics including robotics and automation, operating systems, and digital communications. The course includes an examination of social issues arising from the application of robotics and automation technologies.

An introduction to game development and programming in a 3D animation environment. This includes computer program design, implementation and testing in a high-level, object-oriented programming language. The course also exposes students to problem solving, algorithms, event-driven programming, the building of 3D animated games, the use of application programming interfaces (APIs), and graphics.

Entry level Computing Science course. This course introduces the student to the basic concepts of information technology and computer applications. The student will learn how to use a microcomputer operating system effectively with emphasis on file management. Upon completion of the course the student should be proficient in using and customizing various software packages including word processor, spreadsheet, presentation software and data base software. The course also covers basic uses of the Internet and issues of security and privacy connected to it. The course serves as a preparation for the International Computer Driving License certification.

An introduction to the principles and practices of writing quality code, for students with little or no prior coding experience. Students learn to apply a suite of fundamental principles and strategies for thinking clearly about problems, managing complexity, and designing creative, structured solutions. Students learn to develop the data structures and algorithms to express their solutions, to evaluate and test their designs, and to code them in a modern, high-level programming language, such as Python.

An introduction to computational techniques applied to Engineering problems. The primary focus of the course is on computer systems, the development of algorithms, and computer program design, implementation, and testing. The course also exposes students to the wider discipline of computer science, with topics including computer hardware and software, representation and manipulation of data, numerical analysis, and device interfaces.

An introduction to the development of algorithms, computer program design, program implementation and testing in a high-level, object-oriented programming language. The course also exposes students to event-driven programming, the building of graphical user interfaces (GUIs) and the use of application programming interfaces (APIs) and graphics.

A study of the application of object-oriented programming concepts to the design of software of an intermediate level of difficulty. Advanced object-oriented programming features and techniques are employed. Introduction to data structures, sorting and searching algorithms.

An introduction to the Java programming language for students with previous programming experience in another high-level language. Topics include the Java language and API, object-oriented design and programming, event-driven programming, and graphical user interfaces.

The goal of this course is to introduce students, with little or no previous computer programming or web design experience, to the basic concepts underlying the Internet and computer programming for the web. Students will develop a broad understanding of how the Internet and World Wide Web work, how to create full-featured web sites, and learn the basics of Web programming.

This course provides an overview of the discipline of Computer Science and its fundamental building blocks that unify hardware, software, algorithms and computational theory. It provides the foundation for further studies in computer architecture, operating systems, Net-centric computing, programming languages, compiler design, databases, theory of computation and artificial intelligence.

A study of frequently used data structures and algorithms for manipulating them. This course emphasizes abstract data types and generic abstraction in object-oriented programming. Topics include lists, stacks, queues, sets, tables, trees and graphs, recursion, searching, sorting and analysis of algorithms.

An introduction to some fundamental concepts of computer design and architecture: data representation and coding, combinational and sequential digital logic, microprocessor operation, memory organizations and addressing schemes, instruction sets, assembly language, and operating system interfaces.

A study of the architecture and organization of current microprocessor-based computers, relating the instruction set architecture at the programmer's level of abstraction to the digital logic implementation at the hardware designer's level of abstraction.

An introduction to the concepts and practice of software engineering: systems analysis, user interface design, debugging, profiling, and testing methods, operating system interface, support tools and scripting languages, project management, user and system documentation.

Computational Science is considered by many the “third pillar” of scientific enquiry, alongside theory and physical experimentation. It combines computer simulation, scientific visualization, mathematical modeling, computer programming, data structures and algorithms to offer insights into a wide range of problems. Students are introduced to the principles, concepts, approaches, technologies, and practices of computational science. Students learn practical simulation and computational experimentation skills. The course focuses on the application of these techniques in a wide range of domains, including economics, biology, and the physical and social sciences; and includes an introduction to complexity science, systems thinking, and dynamic systems.

This course continues the development of methods for general modular program design from COMP 120. An emphasis is placed on specific algorithms and data structures which are applicable to a range of problems and techniques for analyzing algorithms and data structures in relation to program design.

This course provides an exposé of current and emerging digital technologies and their impacts on individuals and society. Students learn some of the underlying principles and inner workings of digital technology. They link this understanding to the ramifications of digital technology on a range of economic, legal, environmental, and ethical issues, such as privacy and freedom of expression, security and crime, the nature of work and money, pollution and resource use, and intellectual property rights. Students learn to think critically about technologies, and to argue effectively about their potential impacts.

Students are introduced to the principles, concepts, approaches, technologies, and practices of data modelling and database design using relational, non-relational, and filesystem-based data management systems. Students learn practical query languages and to develop programs that interact with various data management systems. The course focusses on the practical application of these technologies and techniques in a range of domains, including science, business, and computing; and includes an introduction to big data, data governance, and data security.

Students are introduced to the principles, concepts, approaches, technologies, and practices of automated data acquisition, cleaning, transformation, merging, matching, storage, and analysis. Students learn to apply scripting languages to pattern matching, data pipelines, and other data wrangling techniques. The course focusses on practical uses for these technologies and techniques in a range of domains, including science, business, and computing; and includes an introduction to operating systems, command line shells, filesystems, and file formats.