Students learn the basics of problem investigation by conducting research. Students work in a team on a project to learn how to identify and formulate research problems, conduct critical appraisal of existing literature, develop questions and hypotheses, prototype, data analysis and visualization, interpretation of results, formal presentation of the project and technical report writing.
Introduction to the concepts of software engineering: software life cycle, project planning and estimation, Computer Aided Software Engineering (CASE) tools, software requirements elicitation, analysis and specification, design, implementation, testing techniques, software maintenance, risk assessment, and documentation standards.
Physics of semiconductors including crystal structure, conductivity, photoelectric effect, Hall effect, atomic energy levels and band theory, Fermi-Dirac statistics and density of states, intrinsic and extrinsic properties. The physics of common semiconductor devices are also discussed.
Probability and relative frequency; joint probabilities of related and independent events; Bayes’ Theorem; statistical independence; random variables; cumulative distribution functions; probability density functions; parameters describing the central tendency and dispersion of distribution; probability distribution functions in engineering; law of large numbers; central limit theorem; testing hypotheses and goodness of fit; sampling theory; linear correlation and regression.
Fundamentals of statics, dynamics and mechanics of materials with applications to engineering problems.
Definition of the economic problem. Theory of the firm. Theory of competitive supply. Theory of demand. Monopoly and other market forms. Markets for land, labour, and capital. Income distribution. National income determination and causes of unemployment and inflation. Economic fluctuations and growth. International trade. Flexible and fixed foreign exchange rates. Canadian economic problems and policies.
Basic principles of Software Performance Engineering (SPE) are introduced. Topics include introduction to software performance using UML, software performance engineering models, software execution models, system execution models, performance oriented design, performance testing, performance solution, performance tuning and applications.
Use of object oriented approaches to solve GUI problems. Topics include object oriented concepts including inheritance, polymorphism, exception handling and GUI design techniques.
Numerical method algorithms for modeling and solving engineering problems with a predictable error rate. Topics include numerical calculus, optimization, initial value problems, boundary value problems, and the software development of these algorithms.
Hardware and software aspects of microcontrollers and their applications in embedded systems; assembly language programming; architecture and addressing structures; serial and parallel input/output interfaces; timer programming; memory interfacing; interrupts and interrupt service routines; programming in C for microcontrollers; ADC, DAC and sensor interfacing.
An introduction to university-level standards of composition, revision, editing, research, and documentation. A review of English grammar (word and sentence level) and rhetorical forms (paragraph level and beyond), and a study of the methods and conventions of academic argumentation and research, with an emphasis on finding and evaluating sources, formulating research questions, developing arguments, and composing various types of analyses including academic essays.
Basic electronic materials-physical concepts; semiconductor materials; principles of operation of semiconductor devices-diodes and transistors; fundamentals of DC and AC circuit analysis; concepts of magnetism; principles of DC and AC machines and transformers; safety considerations; operational amplifiers and their applications.
Basic set theory. Introduction to logic and proofs. Functions and relations. Mathematical induction and recursion. Algorithms; time estimates and orders of magnitude. Basic combinations. Graphs. Boolean algebras.
The design and analysis of data structures and algorithms including Stacks, Link Lists, Trees, Graphs, Searching, Sorting and their complexity analysis. The theory is reinforced by working examples, laboratories, projects, and the use of abstract data types from the C and C++ standard libraries.
Substantially extends the programming skills development, with more complex programs, using advanced C and C++ features. Good programming style and documentation are stressed throughout. Advanced data types, program structures and other advanced topics in C and C++ languages are discussed.
A first course in programming given in C – mathematical problem solving, program development, C grammar and simple system functions. Students will develop and write their own programs and run them in a time-sharing environment.
Introduction to fundamental concepts of digital logic circuits and design with Verilog HDL. Topics include principles of number systems, operations, codes, logic gates, Boolean algebra and logic simplification, PAL and PLD based combinational logic functions, synchronous and asynchronous logic circuits, state transition diagrams, latches, flip-flops, counters, shift registers, memory, Mealy and Moore finite state machines.
Layered protocol architecture; data-link control including error control and flow control; circuit switching and packet switching; bridging and routing; local area networks, internetworking; TCP/IP architecture and addressing structure; network management.
Applications of integration, introduction to multiple integrals sequences and series; power series.
An introduction to the fundamental principles involved in the management of organizations. Specific emphasis is placed on the functions of management related to the planning, organizing, decision-making and controlling of organizational activities. Provides an overview of the dynamic relationships which exist between the many components which comprise the whole organization. Systems theory is used to develop a framework which can be used to illustrate these relationships. Course content covers: technology and organization, decision-making, management of human resources, and interactions with the environment.
The first part of the course is an introduction to matrix algebra. Solutions of simultaneous equations. Gaussian elimination. Vector and matrix notation. Determinants. Linear independence. Eigenvectors and diagonalization. The second part of the course is an introduction to probability and statistics. Simple ways of analyzing data. Concept of probability. Discrete and continuous probability. Point and interval estimation. Significance tests. Regression and correlation analysis.
An introductory course in ordinary differential equations. First order differential equations; exact equations; separation of variables, integrating factors, linear and non-linear equations, higher order differential equations, linear, constant co-efficients, homogeneous, non-homogeneous. Systems of differential equations, Laplace transforms, series solution. The emphasis is on applications to engineering problems.
More courses will be added on this page once registration for next year is open.
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