Computer Science (Sci): Finite automata, regular languages, context-free languages, push-down automata, models of computation, computability theory, undecidability, reduction techniques.

Offered by: Computer Science

• 3 hours
• Prerequisite: COMP 251.

• Terms
  • Fall 2024
  • Winter 2025
• Instructors
  • J茅r么me Waldispuhl
  • Mathieu B茅rub茅-Valli猫res

Computer Science (Sci): Computer representation of numbers, IEEE Standard for Floating Point Representation, computer arithmetic and rounding errors. Numerical stability. Matrix computations and software systems. Polynomial interpolation. Least-squares approximation. Iterative methods for solving a nonlinear equation. Discretization methods for integration and differential equations.

Offered by: Computer Science

• 3 hours
• Prerequisites: MATH 222 and MATH 223 and one of: COMP 202, COMP 208, COMP 250; or equivalents.
• Restrictions: Students cannot receive credit for both COMP 350 and MATH 317.

• Terms
  • Fall 2024
• Instructors
  • Xiao-Wen Chang

Computer Science (Sci): Characteristics and utility of concurrent programs; formal methods for specification, verification and development of concurrent programs; communications, synchronization, resource allocation and management, coherency and integrity.

Offered by: Computer Science

• 3 hours
• Prerequisites: COMP 251, COMP 302, and COMP 310 or ECSE 427

• Terms
  • Winter 2025
• Instructors
  • Clark Verbrugge

Computer Science (Sci): Introduction to search methods. Knowledge representation using logic and probability. Planning and decision making under uncertainty. Introduction to machine learning.

Offered by: Computer Science

• 3 hours
• Prerequisites: (COMP 206 or ECSE 321), MATH 323 or equivalent and COMP 251.
• Restriction: Not open to students who have taken or are taking ECSE 526.

• Terms
  • Fall 2024
• Instructors
  • David P Meger, Golnoosh Farnadi

Electrical Engineering: Design principles of autonomous agents, agent architectures, machine learning, neural networks, genetic algorithms, and multi-agent collaboration. The course includes a term project that consists of designing and implementing software agents that collaborate and compete in a simulated environment.

Offered by: Electrical & Computer Engr

• (3-0-6)
• Prerequisite: ECSE 324
• Restriction: Not open to students who have taken or are taking COMP 424.

• Terms
  • Fall 2024
• Instructors
  • Jeremy Cooperstock

Computer Science (Sci): The structure of a compiler. Lexical analysis. Parsing techniques. Syntax directed translation. Run-time implementation of various programming language constructs. Introduction to code generation for an idealized machine. Students will implement parts of a compiler.

Offered by: Computer Science

• 3 hours, 1 hour consultation
• Prerequisites: COMP 273 and COMP 302

• Terms
  • Winter 2025
• Instructors
  • Christophe Dubach

Computer Science (Sci): Use of computer in solving problems in discrete optimization. Linear programming and extensions. Network simplex method. Applications of linear programming. Vertex enumeration. Geometry of linear programming. Implementation issues and robustness. Students will do a project on an application of their choice.

Offered by: Computer Science

• 3 hours
• Prerequisites: COMP 360 and MATH 223

• Terms
  • This course is not scheduled for the 2024 academic year
• Instructors
  • There are no professors associated with this course for the 2024 academic year

Electrical Engineering: Modelling and simulation of control systems; basic concepts of linear systems; open and closed loop control; classical design of controllers - specifications in the step response and the frequency domain; state space design of controllers - pole placement and LQR; sampled data systems.

Offered by: Electrical & Computer Engr

• (3-1-5)
• Corequisite: ECSE 304 or ECSE 306

• Terms
  • This course is not scheduled for the 2024 academic year
• Instructors
  • There are no professors associated with this course for the 2024 academic year

Electrical Engineering: Discrete-time signals and systems; Fourier and Z-transform analysis techniques, the discrete Fourier transform; elements of FIR and IIR filter design, filter structures; FFT techniques for high speed convolution; quantization effects.

Offered by: Electrical & Computer Engr

• (3-2-4)
• Prerequisite(s): ECSE 206 or ECSE 304 or ECSE 306.
• Tutorials assigned by instructor.

• Terms
  • Fall 2024
• Instructors
  • Benoit Champagne

Computer Science (Sci): Fundamental design principles, elements, and protocols of computer networks, focusing on the current Internet. Topics include: layered architecture, direct link networks, switching and forwarding, bridge routing, congestion control, end-to-end protocols application of DNS, HTTP, P2P, fair queuing, performance modeling and analysis.

Offered by: Computer Science

• 3 hours
• Prerequisite: COMP 310 or ECSE 427

• Terms
  • Winter 2025
• Instructors
  • Mona E Elsaadawy

Electrical Engineering: Definition, structure and properties of embedded systems. Real-time programming: interrupts, latency, context, re-entrancy, thread and process models. Microcontroller and DSP architectures, I/O systems, timing and event management. Real-time kernels and services. Techniques for development, debugging and verification. Techniques for limited resource environments. Networking for distributed systems.

Offered by: Electrical & Computer Engr

• (3-1-5)
• Prerequisites: ECSE 324

• Terms
  • Winter 2025
• Instructors
  • Jeremy Cooperstock

Electrical Engineering: Introduction to fault-tolerant systems. Fault-tolerance techniques through hardware, software, information and time redundancy. Failure classification, failure semantics, failure masking. Exception handling: detection, recovery, masking and propagation, termination vs. resumption. Reliable storage, reliable communication. Process groups, synchronous and asynchronous group membership and broadcast services. Automatic redundancy management. Case studies.

Offered by: Electrical & Computer Engr

• (3-1-5)
• Prerequisites: ECSE 324 and (ECSE 250 or COMP 250)

• Terms
  • This course is not scheduled for the 2024 academic year
• Instructors
  • There are no professors associated with this course for the 2024 academic year

Electrical Engineering: The course highlights human-computer interaction strategies from an engineering perspective. Topics include user interfaces, novel paradigms in human-computer interaction, affordances, ecological interface design, ubiquitous computing and computer-supported cooperative work. Attention will be paid to issues of safety, usability, and performance.

Offered by: Electrical & Computer Engr

• (3-4-2)
• Prerequisites: (ECSE 324 and ECSE 250) or (ECSE 324 and COMP 250) or (COMP 251 and COMP 273)

• Terms
  • Fall 2024
• Instructors
  • Jeremy Cooperstock

Electrical Engineering: Trends in technology. CISC vs. RISC architectures. Pipelining. Instruction level parallelism. Data and Control Hazards. Static prediction. Exceptions. Dependencies. Loop level paralleism. Dynamic scheduling, branch prediction. Branch target buffers. Superscalar and N-issue machines. VLIW. ILP techniques. Cache analysis and design. Interleaved and virtual memory. TLB translations and caches.

Offered by: Electrical & Computer Engr

• (3-1-5)
• Prerequisites: ECSE 324
• Tutorials assigned by instructor.

• Terms
  • Winter 2025
• Instructors
  • Amin Emad

Electrical Engineering: Introduction to current microprocessors, their architecture, programming, interfacing and operating systems. The course includes lectures, use of crossassemblers, and simulators as well as laboratory experiments on actual microprocessor hardware.

Offered by: Electrical & Computer Engr

• (1-5-3)
• Prerequisites: (CCOM 206 or WCOM 206) and ECSE 323.
• This course may be counted as a technical complementary or a lab complementary.
• Limited Enrolment (50)
• Lab hours assigned by instructor.

• Terms
  • This course is not scheduled for the 2024 academic year
• Instructors
  • There are no professors associated with this course for the 2024 academic year

Electrical Engineering: Fundamental mathematical, algorithmic and representational issues in computer graphics: overview of graphics pipeline, homogeneous coordinates, projective transformations, line-drawing and rasterization, hidden surface removal, surface modelling (quadrics, bicubics, meshes), rendering (lighting, reflectance models, ray tracing, texture mapping), compositing colour perception, and other selected topics.

Offered by: Electrical & Computer Engr

• (3-0-9)
• Prerequisite: ECSE 324

• Terms
  • Fall 2024
• Instructors
  • Paul Kry

Computer Science (Sci): Fundamental mathematical, algorithmic and representational issues in computer graphics: overview of graphics pipeline, homogeneous coordinates, projective transformations, line-drawing and rasterization, hidden surface removal, surface modelling (quadrics, bicubics, meshes), rendering (lighting, reflectance models, ray tracing, texture mapping), compositing colour perception, and other selected topics.

Offered by: Computer Science

• 3 hours
• Prerequisite: MATH 222, MATH 223, COMP 250, COMP 206

• Terms
  • Fall 2024
• Instructors
  • Paul Kry