CAS 701

Logic and Discrete Mathematics

Graduate The course will cover some of the material encountered at the undergraduate courses on logic and discrete mathematics as well as advanced material on topics such as proof systems, sets, relations, and functions, recursion, type theory, and first and higher order logic systems. There will be emphasis on topics related to computer science and software engineering.

CAS 702

Data Structures and Algorithms

Graduate The course will cover some basic material encountered at the relevant undergraduate courses on data structures and algorithms plus more advanced material on topics such as network flows, linear programming, computational geometry and NP-completeness. There will be emphasis on techniques such as greedy and dynamic programming. Amongst other topics, the course covers the following: • Binomial heaps, an example of worst-case analysis • Amortized analysis • Fibonacci heaps, an example of amortized analysis • Hash tables, an example of randomized analysis • Greedy algorithms and matroids • Dynamic programming and all-pairs shortest paths • Maximum flow • Linear Programming and Duality •Primal-Dual schema as an algorithmic design tool • Approximation algorithms

CAS 703

Software Design

Graduate Formal specification methods. Requirements specifications. Fail-safe systems. Verification of safety critical applications. Systematic testing. Specification and design of concurrent, multiprocess and distributed systems.

CAS 704

Embedded, Real-Time Software Systems

Graduate 1. Scheduling a. Time-based scheduling b. Classical results for single processor scheduling algorithms c. Multiprocessor scheduling d. Scheduling with energy concerns The rest of the course coverage will be filled in after a vote of the class. The following are all possibilities. 2. Real-Time Operating Systems – we can look at TinyOS, details of its implementation and some applications. 3. Fault Tolerance Techniques 4. State-Space Control Theory and Real-Time Implementation 5. Specification of Real-Time Systems (examine in detail one framework – UML, Timed Petri Nets, etc.) 6. Individual Student Presentations – allows you to explore and present a topic of your choice.

CAS 705

Computability and Complexity

Graduate Computability: Finite automata, Turing machines, and recursive functions. The Halting problem and the Church-Turing thesis. Complexity: Classes defined in terms of time, space, and circuits. The reachability method. The P vs. NP problem, Cook’s theorem, and NP-completeness. The Time and Space Hierarchy theorems. Randomized and parallel computations.

CAS 706

Programming Languages

Graduate Design, definition and implementation of programming languages. Programming language paradigms; syntax, attribute grammars, typing; axiomatic, operational and denotational semantics; correctness proofs; implementation techniques, virtual machines; design and implementation of Domain-Specific Languages.

CAS 707

Formal Specification Techniques

Graduate Pre/Postconditions, refinement, state-based approaches, event based approaches, algebraic specifications, Petri nets, temporal logic, properties of programs, and specification, verification, and validation.

CAS 708

Scientific Computation

Graduate Floating-point arithmetic, solutions of systems of linear equations by direct and iterative methods, sparse matrix algorithms, solving systems of nonlinear equations, integration, differentiation, eigenvalue problems, methods for initial value problems in ordinary differential equations, and automatic differentiation.

CAS 720

Foundations of Future Resilient Databases

Graduate The field of databases is ever evolving. Recent directions include the development of resilient database systems based on blockchain technology that can deal with failures and enable cooperative data management. In this course, we will provide an introduction to this area, starting with a basic treatment of consensus-based transaction processing and with a further focus on selected topics. . The course assumes a pre-existing knowledge of databases and discrete mathematics at an undergraduate level (e.g., COMPSCI 3DB3 and COMPSCI 2DM3). Note: although this course will cover some blockchain-related topics, this course is not about cryptocurrencies.

CAS 721

Combinatorics and Computing

Graduate Topics in applied combinatorics and graph theory of importance to both theoretical computer science and practical computing including combinatorial computing. Main topics: graph theory and algorithms, combinatorial optimization and algorithms, design theory and coding theory. Solving problems in finite combinatorics using computers.

CAS 722

Computing Patterns in Strings

Graduate This course deals with algorithms for finding “patterns” in strings, patterns of three main kinds: specific, generic, and intrinsic. The importance of approximate patterns and algorithms which identify them is made clear. Applications to DNA sequence analysis and other scientific areas are emphasized.

CAS 723

Human-Robot Interaction

Graduate Robots are becoming more common in places such as hospitals, museums, airports, workplaces, schools, and homes. Thus, it is important to consider how people will interact and communicate with robots. Robots pose unique challenges in comparison to the more familiar interfaces of PCs and hand-held devices: robots often have limited display space, move dynamically about an environment, and elicit responses more akin to humans than to other technologies. As such, interaction often includes a mixture of modalities such as gestures, speech, control interfaces, and even human-like facial expressions. In this course, students will learn about interaction design challenges specific to robots and emerging methods for understanding and approaching human-robot interaction design.

CAS 724

Concurrency Theory

Graduate Models based on interleaving and partial order paradigms including the Calculus of Communicating Systems (CCS), Communicating Sequential Processes (CSP), Actors, Petri Nets, Pomsets and COSY. Basic properties of concurrent systems such as deadlock, liveness, safety, fairness, etc. Temporal Logic techniques. The growing role of concurrent systems in many diverse scientific and engineering activities will also be discussed.

CAS 725

Formal Methods of Real-Time Systems

Graduate Introduction to formal methods including equivalence verification, model-checking and theorem proving. Emphasis on verification of safety-critical real-time control systems using automated theorem provers and simple programming techniques.

CAS 726

Robot Learning

Graduate This course provides an in-depth exploration of applications of machine learning to autonomous systems. The course will assume basic familiarity with modern supervised machine learning methods. The first part of the course will introduce the classical probabilisitic modelling approach to autonomous systems and robotics. In the second part of the course we will investigate particular applications of machine learning within the classical framework, focusing on perception and planning. In the final part of the course we will introduce the basics of reinforcement learning and investigate applications to autonomous systems.

CAS 728

Computability on Abstract Data Types

Graduate N/A

CAS 733

Mobile User Interface Design

Graduate An advanced look at User Interface issues associated with mobile devices, e.g. smart phones. This course is for graduate students who have already taken a course in human-computer interaction and already know how to program non-trivial applications on at least one mobile device. Through literature review, and experimentation, students will learn how the advent of mobile devices is changing our approach to human-computer interactions, and will practice a quantitative approach to evaluating the effectiveness of user interface concepts.

CAS 734

Formalized Mathematics

Graduate Computer-supported, formalized mathematical reasoning for practical applications. Specification and verification in higher-order logic. Interactive theorem proving systems. Techniques for developing axiomatic theories.

CAS 735

(Micro)service-oriented architectures

Graduate The design of distributed applications triggers software architectures challenges at different levels. This course will focus on the definition of “business-oriented services” at the architectural level, from their inception to their deployment into a production environment. This class aims to cover selected topics related to (micro-)service-oriented architectures, architectural patterns for distributed applications, service portfolio management and operational deployment of distributed systems. Students will be exposed to the technical dimension of such systems and state-of-the-art research in this domain. The course assumes a pre-existing knowledge of how to design and test pieces of software (e.g., undergrad course on these topics).

CAS 736

Analysis of Stochastic Networks

Graduate Techniques for the analysis of large networks that can be modeled in a statistical manner. Single queues, product form networks and mean value analysis. Fluid and diffusion approximations. Simulation techniques, including variance reduction. Hybrid simulation. Current research directions in Stochastic networks.

CAS 737

Computer Animation

Graduate Computer animation has been widely used in AR/VR applications, game development and entertainment industry. The goal of this course is to provide knowledge in different aspects of computer animation area for research and development purposes. This course will first introduce the fundamentals of computer animation, then further delve into kinematics, rigging, skinning and blendshapes for animating characters. It will cover classic motion capture, synthesis and editing techniques, as well as state-of-the-art research in animation area using deep learning, reinforcement learning and physics simulations. To take this course, students are expected to have prerequisite knowledge in Linear Algebra, Geometry, Data Structure and programming.

CAS 738

Algebraic Methods in Software Engineering and Computer Science

Graduate The course covers a variety of software development issues, and illustrates the versatility of algebraic methods when used as conceptual tools in the software development process. The topics include algebraic approaches to software requirements, design, program verification, testing, and security. Several algebraic structures, such as relation algebra, Kleene algebra, and product family algebra, are introduced and discussed within software related issues.

CAS 739

Evolutionary Computation

Graduate Evolutionary computation is a family of wildly creative algorithms that draw inspiration from genetics and natural selection. This course investigates the history and theory of evolutionary computation with a focus on applications in search and optimization. Hands-on programming experiments and readings from the literature will introduce key principles and place evolutionary methods in context with the broader realm of bio-inspired computing in machine learning and artificial life.

CAS 740

Numerical Methods for Ordinary Differential Equations and Differential-Algebraic Equations

Graduate Numerical methods for ODEs and DAEs; Runge-Kutta, multistep methods; convergence, accuracy, consistency; error estimation and propagation, step size and order control; stability, non-stiff and stiff methods; software for ODEs and DAEs.

CAS 741

Development of Scientific Computing Software

Graduate This course presents the basic principles of software development for reliable scientific and engineering software. Using example applications, a systematic process is given for the development and documentation of requirements, high-level design, module design, implementation, testing and inspection.

CAS 743

Functional Programming

Graduate The powerful abstraction capabilities and clean semantics of functional programming languages improve programmer efficiency and facilitate correct program derivation and transformation. This course will present practical aspects of software development in modern functional programming languages and theoretical foundations, like term rewriting systems, lambdacalculi, and type systems.

CAS 744

Advanced Topics in Design of Algorithms

Graduate Advanced design techniques for algorithms, including (but not limited to): approximation algorithms, randomized algorithms, on-line computation and competitive analysis, quantum computing. Each term the course will concentrate mainly on one of these topics for a deeper understanding of the particularities and the defining problems/issues of the field as well as its applications to other fields and to practice. Presentation of up to date results and tackling of open research problems will be the main requirement for the students taking this course.

CAS 745

Supervisory Control of Discrete-Event Systems

Graduate This course is an introduction to the control of discrete-event systems (DES), asynchronous systems discrete in space and time (e.g. manufacturing systems, communication systems, etc.). The course will provide a solid foundation for research in this area, focusing on architectural issues such as modular, decentralized, and hierarchical control. The course will also discuss timed DES, as well as current topics of interest.

CAS 746

Advanced Topics in Combinatorial Optimization

Graduate This course provides an introduction to useful frameworks for discrete optimization problems. We introduce the basic concepts of polyhedra, lattices and integer cones and illustrate these notions by some examples coming from combinatorial optimization. An algorithm for finding the Hermite normal form of a lattice and the main methods for facet or vertex enumeration are presented. http://www.cas.mcmaster.ca/~deza/cas746_18.html

CAS 747

Machine Learning on Graphs

Graduate Complex data in the real-world can often be represented as a graph of relationships between objects or entities. This course focuses on the computational, algorithmic and modeling challenges related to the analysis of large scale graphs and networks. Students will be introduced to machine learning techniques and data mining tools that reveal insights on a variety of graphs and networks. Topics include: graph representation learning, graph neural networks, algorithms for complex networks, reasoning over Knowledge Graphs, influence maximization, and social network analysis.

CAS 748

Analysis and Synthesis of Sound

Graduate Sound as signals (Fourier Analysis, basic harmony theory), Sound analysis (filters, FFT), Synthesis (band limited signals), over-sampling, real-time signal processing, user interfaces (real time interaction with algorithms), vocoders, physical modeling (fast DSP algorithms to solve PDE’s).

CAS 749

Advanced Topics in Computational Geometry

Graduate This course provides an introduction to useful frameworks for computational geometry problems in dimension 2, 3 and higher. We introduce the basic concepts of triangulations, Voronoi diagrams, polyhedra, lattices and integer cones, arrangement of hyperplanes and linear programming and illustrate these notions by some examples coming from combinatorial optimization.

CAS 750

Model-Based Image Reconstruction

Graduate An overview of three themes in advanced image processing: functional analysis (e.g., Fourier, Wavelet and SVD methods), PDEs (e.g., anisotropic diffusion), optimization of statistical models (e.g. Total Variation regularization). And, a detailed look at specific methods and techniques for applying these methods in new areas: medical imaging, visual process control. Including all phases of application development from mathematical modeling, through complexity analysis.

CAS 751

Information-Theoretic Methods in Trustworthy Machine Learning

Graduate The interplay between information theory and computer science is a constant theme in the development of both fields. This course discusses how techniques rooted in information theory play a key role in (i) understanding the fundamental limits of classical high-dimensional problems in machine learning and (ii) formulating emerging objectives such as generalization bounds, privacy, fairness, and interpretability. The course begins with an overview of important concepts in information theory such as channel capacity and rate-distortion theory, and then touches upon recent advances in: minimax estimation risk and sample complexity, generalization, differential privacy, algorithmic fairness, model interpretability, and explainability. No background in information theory is required, but some knowledge of machine learning, statistics and probability (equivalent to undergraduate courses in the topic) are needed.

CAS 754

Programming Methodology

Graduate Verification and Refinement Methods for Sequential and Concurrent Programs, Specification Techniques, Reliability, Object-Orientation (Modeling, Design, Patterns, Concurrency), Program Design and Program Documentation, Tools and Compilers.

CAS 756

Advanced Topics in Formal Methods and Software Architecture

Graduate The course presents advanced techniques for formal specification of requirements, designs and implementations of software based systems, focusing on software architecture as the organi sing principle for software development. Course content will include some topics amongst: comparative properties of formalisms for specification; meta-properties of specification formalisms, including interpolation properties, modularity and their relationships; component based approaches and the role of category theory in component composition; formalisation of encapsulation, cohesion and coupling; externalisation of interaction definition; formal toolkit for software architecture.

CAS 758

Advanced Compiler Design and Optimization

Graduate Advanced compiler design methodologies with emphasis on control and data flow analyses, code optimization and related issues. http://www.cas.mcmaster.ca/~franek/courses/cas758/

CAS 760

Logic for Practical Use

Graduate Attributes of a practical logic. Techniques for improving the practicality of traditional logics. Design, implementation, and use of practice-oriented logics.

CAS 761

Generative Programming

Graduate Generative programming has recently graduated from an old technique for very specific tasks (like parser generators) to a general purpose tool. It has clear applications to model-driven software engineering, software product families and feature-oriented programming. It is also finding increasing applications in embedded systems. Unlike other programming paradigms, a proper scientific study of generative programming has only been started quite recently, and introductory material is still sparse. Topics: generative programming techniques (metaprogramming, templates, staged computation, etc). Domain specific languages. Applications to software product families and software product lines. Domain analysis and feature modelling. If time permits, constraint-based approaches and transformation systems. After taking the course, the students will be able to perform domain analysis and design, and implement program generators using a number of different technologies. The course will be conducted through student-led discussions of important papers in the domain.

CAS 763

Certified Programming with Dependent Types

Graduate Type systems featuring types depending on values empower not only logics that can capture common mathematical formalizations more naturally than conventional first-order or higher-order logics; they also empower programming languages where specifications may be incorporated into the type of programs, and well-typed programs are thus guaranteed to satisfy these specifications. Students will learn at least one dependently-typed programming language in depth. The course will also cover associated foundations, including relevant type theories and the Curry-Howard correspondence, as well as useful patterns of formalizing, programming, and proving in dependently-typed programming languages.

CAS 764

Advance Topics in Data Management

Graduate Systems and users are generating increasing amounts of heterogeneous data from diverse sources (e.g., system logs, sensor networks, databases, medical records, tweets, etc). To extract value from these datasets (via querying and analysis) first requires data preparation to clean, transform, and enrich the raw data into a structure that is desirable for analysis. The challenges of managing large-scale, heterogeneous, poor quality, and fast data, go beyond the capabilities of traditional database systems.   This course will explore data-intensive applications, and the algorithms that are needed for different data management tasks.

CAS 765

Wireless Networking and Mobile Computing

Graduate This course introduces fundamental concepts, state-of-the-art research and applications of wireless networking and mobile computing. Topics covered include wireless network protocols, wireless standards, location-based services and techniques, security, and programming on mobile platforms.

CAS 766

Concurrent Programming

Graduate Processes and Synchronization, Atomicity, Mutual exclusion, Locks and Barriers, Semaphores, Monitors, Message Passing, Parallel Programming, Patterns for Concurrency, Transactional Memory, Linearizability, Consensus, Lock-free Algorithms, Multi-core Processors, Heterogeneous Computing with GPU and FPGA, Applications.

CAS 767

Information Privacy and Security

Graduate This course covers issues and technologies in Information Privacy, Security, and Accountability. The course surveys cryptography, digital signature, key management, authentication, certificates, PKI, Application layer Access control policies and mechanisms, data forensics, Internet security protocols, trust management, information and web privacy, privacy and data aggregation, audit log mechanisms, privacy policy expression and enforcement, Differential Privacy, Security and privacy in healthcare, Social networking security and privacy, Usable security and privacy, and privacy-enhancing technologies. Students will undertake a project that employs and integrates these technologies.

CAS 768

Development and Certification of Safety-Critical Software Intensive Systems

Graduate Safety-critical systems are becoming more and more part of our everyday lives – cars, planes, trains, medical devices and nuclear power plants are obvious examples of safety-critical systems. Most of these systems depend on software for their correct functioning. This course is about building and certifying such systems. The emphasis is on the software component(s).

CAS 771

Introduction to Big Data Systems and Applications

Graduate Nowadays, unstructured data such as multimedia data account for around 80% of Internet traffic. Meanwhile, more than 80% of potentially usable business information exists in unstructured formats (e.g., audio/video information, social network relations, users’ purchasing habits, environmental data). Much of the unstructured data remains unused because the algorithms available for analyzing and understanding unstructured data usually do not scale up to handle the amount of data being generated. This course will discuss and explore the computer system design to deal with large scale unstructured data.

CAS 772

Mobile Data Analytics

Graduate With the prevalence of wireless technologies and broadband access, untethered mobile and wearable devices have become an essential part of everyday life. The deluge of multimodality, high volume, streaming and in some cases unstructured spatial-temporal data from mobile devices poses serious challenges to algorithm and system design to extract timely information and actionable items. This class aims to cover selected topics on data acquisition, sensor signal processing, machine learning techniques, data management and processing systems pertaining to mobile data analytics as well as state-of-the-art research in this area.

CAS 774

Foundations of Machine Learning

Graduate The course starts off by introducing a standard mathematical model (i.e,. the PAC model) for studying machine learning problems. The first half of the course is then dedicated to understanding this model, characterizing “learnability” within this model, and establishing the foundations of Computational Learning Theory. The main topics here include sample complexity, VC dimension, No-Free-Lunch Theorem, and the Fundamental Theorem of Learning. The primary textbook for this part of the course is “Understanding Machine Learning: From Theory to Algorithms” By Shai Shalev-Shwartz and Shai Ben-David. In the second half of the course, various tasks and algorithms are studied and analyzed via the lens of the proposed theoretical foundations. These topics include Distribution Learning, Learning via Compression, and Clustering, and Deep Learning.

CAS 775

Foundations Unsupervised Learning

Graduate The main focus of the course is on the modern aspects of distribution learning. The topics include PAC learning of distributions, efficient learning of mixture models, information theoretic aspects of distribution learning, computational complexity distribution learning, models for robust distribution learning, differentially private distribution learning, open questions in modern distribution learning, generative adversarial networks, and variational autoencoders. The course will be mostly based on recent papers, but some introductory aspects can be found in the book titled “Combinatorial Methods in Density Estimation” by Luc Devroye and Gabor Lugosi.

CAS 780

Independent Study in Computing and Software

Graduate Normally a self-study course. Prerequisite: Permission of the Chair of the Department.

CAS 781

Modern Approaches to Game Design

Graduate

CAS 781

Advanced Topics: Machine Learning on Graphs

Graduate Complex data in the real-world can often be represented as a graph of relationships between objects or entities. Such networks are fundamental tools to model technological, biological and social relationships. This course focuses on the computational, algorithmic and modeling challenges related to the analysis of large scale graphs and networks. By studying the underlying graph structure and its features, students will be introduced to machine learning techniques and data mining tools that reveal insights on a variety of graphs and networks. Topics of this course include: graph representation learning, Graph Neural Networks, algorithms for complex networks, reasoning over Knowledge Graphs, influence maximization and social network analysis.

CAS 781

User Interface Frameworks and Programming Languages

Graduate Graphical User Interfaces were developed together with programming languages, specifically object-oriented languages starting with Smalltalk. Since newer interface framework authors wanted to learn from previous frameworks, and make things easier for programmers already familiar with early frameworks, subsequent frameworks went through largely gradual change, and the perception developed that OO languages were the “right” tool for UI frameworks, although lost in this slogan were the differences among OO languages, such as dynamic versus static dispatch. In this seminar course, students will research historical and current UI Frameworks and and build a story about the evolution of UI frameworks and the interaction of those frameworks with the evolution of programming languages. Depending on the number of students, we may only cover “core” languages and frameworks like Smalltalk-80, Swift/UIKit, Elm/GraphicSVG or Java/Swing and based on the knowledge of the students, try to predict the future evolution of UI frameworks based on recent developments in programming languages. Depending on enrolment, we will also contrast the UI framework features which evolved from Smalltalk-80, those which evolved from html, and attempts to create UI frameworks for functional languages.

CAS 781

Advanced Topics: Mobility in the Aging Population (Part II)

Graduate The proportion of older adults (aged 65 and older) worldwide has been increasing steadily over the past 40 years. In Canada, it has been projected that seniors will represent up to 25% of the total population by 2036. Mobility is a crucial indicator of functional status, and a predictor of quality of life and longevity; hence, it is often called the sixth vital sign. Mobility encompasses not only the physical activities of older adults, and the performance of specific maneuvers such as sit-to-stand, walking or climbing stairs, but also participation in society (e.g., the ability to drive, accessibility to public transportation). This course (MiA II) is the second installment of a two-part 6-unit credit course that spans two terms. The main goals of MiA II are 1) to put in practices principles and tools learned from MiA I in group design projects, 2) to work in an interdisciplinary team, and 3) to develop a technical solution with real-world impacts.

CAS 781

Advanced Topics: Mobility in the Aging Population (Part I)

Graduate The proportion of older adults (aged 65 and older) worldwide has been increasing steadily over the past 40 years. In Canada, it has been projected that seniors will represent up to 25% of the total population by 2036. Mobility is a crucial indicator of functional status, and a predictor of quality of life and longevity; hence, it is often called the sixth vital sign. Mobility encompasses not only the physical activities of older adults, and the performance of specific maneuvers such as sit-to-stand, walking or climbing stairs, but also participation in society (e.g., the ability to drive, accessibility to public transportation). This course (MiA I) is the first of a two-part 6-unit credit course that spans two terms. This main goals of MiA 1 are to provide students in the CREATE program from diverse backgrounds the necessary foundational knowledge to understand mobility challenges faced by older adults and their physiological roots, user-centric research design and methods in multidisciplinary settings, and key technologies including data management, machine learning, sensors and sensor data analysis, as well as new frontiers in sensing. The lectures will be offered by renown experts in related fields from three institutions.

CAS 781

Advanced Topics: Intermediate Language for Functional Programming

Graduate The paper “Types Are Calling Conventions” (Bolingbroke and Peyton Jones) proposes an intermediate language for use in compilers of functional programming languages based on function types. The goal of this course is to understand the history of intermediate languages for functional programming, the innovations in this paper and subsequent papers, and the challenges to implementing Strict Core, through a parallel effort to summarize the related literature, and build up a toy example.

CAS 781

Advanced Topics- Medical Robotics

Graduate This course will introduce students to the world of medical robots and attempt to redefine how they think about robots. It will provide an in-depth overview of how small-scale robots are designed, fabricated and controlled. Popular remote actuation techniques will be introduced and scaling laws governing these small-scale robots will be discussed. The course will also cover how feedback for medical robots is challenging and the design considerations for integration into larger guidance systems. The Department of Computing and Software does not have a course offering on Medical Robotics. A similar course used to exist in ECE and BME but has not been offered for about 12 years as there has been no faculty around to teach it. Medical Robotics is a growing field and research area and the topics covered here are relevant for students pursuing a future in industry or academia.

CAS 781

Advanced Topics- Time Series Analysis

Graduate We examine a variety of mathematical techniques related to series analysis and prediction. We take two points of view, the signals and systems and the statistical point of view. Topics include, Hilbert spaces, norms and duals, transfer functions, Integral transforms, Wavelets, Markov Models, linear prediction, auto-regression, filtering and smoothing, Bayesian filtering.

CAS 781

Advanced Topics- Computer Vision Med Imaging

Graduate This course will be a systematic study of the modern evolution of computer vision. We will study transformational advances in the area by reading the original publications and applying some of these methods to medical imaging datasets for disease classification and anatomical segmentation.

CAS 781

Advanced topics – Functional Safety of Autonomous Vehicles

Graduate

COMPSCI 6E03

Performance Analysis of Computer Systems

Graduate Use of queuing models and simulation to predict computer system performance and find bottlenecks in a system. Types of models, distributions. Markov models. Modelling storage and network behaviour, locks, critical sections, concurrency. Introduction to analytical system reliability.

COMPSCI 6F03

Distributed Computer Systems

Graduate Parallel architectures, design and analysis of parallel algorithms; distributed-memory, shared-memory and GPU computing; communication cost, scalability; MPI, OpenMP and OpenACC; tuning parallel programs for performance.

COMPSCI 6O03

Linear Optimization

Graduate Linear programming, integer programming, decision trees, network flow problems, graph algorithms, route planning, applications to engineering problems.

COMPSCI 6TB3

Syntax Based Tools and Compilers

Graduate Lexical analysis, syntax analysis, type checking; syntax-directed translation, attribute grammars; compiler structure; implications of computer architecture; mapping of programming language concepts; code generation and optimization.

COMPSCI 6TC3

Recursive Function Theory and Computability

Graduate Recursive and primitive recursive functions, decidability and undecidability with applications to formal language theory, logic and algebra.

COMPSCI 6TE3

Continuous Optimization

Graduate Fundamental algorithms and general duality concepts of continuous optimization. Special attention will be paid to the applicability of the algorithms, their information requirements and computational costs. Practical engineering problems will illustrate the power of continuous optimization techniques.

COMPSCI 6WW3

Web Systems and Web Computing

Graduate World wide web as networks: protocols, clients/servers and social issues; programming systems: markups, scripts, styles; platform technologies; WWW services: standard systems, browser-based, security issues, examples.

MECHTRON 6AX3

Intelligent and Predictive Control

Graduate This course introduces several concepts used in systems engineering, predictive control and artificial intelligence. A variety of techniques including prediction and estimation, linear models, basic optimization techniques, Monte Carlo techniques, neural networks, and clustering are introduced. The techniques are applied to predictive and smart systems by the example of model predictive control and intelligent control, classification and decision making. The course is intended for engineering students with understanding in signals and systems and control.

SFWRENG 6GA3

Real-Time Systems and Computer Game Applications

Graduate Hard and soft real-time systems. Safety classification. Fail-safe design, hazard analysis. Discrete event systems. Modes. Requirements and design specifications. Tasks and scheduling. Clock synchronization. Date acquisition. Applications in real-time networking, quality of service and multimedia.

SFWRENG 6HC3

Human Computer Interfaces

Graduate A study of the principles of good interface design. Information overload problems and accommodating user mental models. Human input and technology insertion methods. Information and data visualization techniques. Modes and the mode awareness problem. Human factors and health issues, ergonomics. Interface design tools and Performance Support Systems.

ASTRON 2B03

The Big Questions

Technical Elective LIST C: SOFTWARE ENGINEERING BASIC SCIENCE ELECTIVES Ultimate questions in modern science are surveyed with emphasis on physical sciences: origin of space-time, elements and structure in the cosmos (stars, planets, galaxies.)

ASTRON 2E03

Planetary Astronomy

Technical Elective LIST C: SOFTWARE ENGINEERING BASIC SCIENCE ELECTIVES Physical and mathematical foundation of planetary astronomy. Historical development of ideas about the solar system. A modern view of the planets; the origin and evolution of the solar system and planets around other stars.

BIOLOGY 1A03

Cellular and Molecular Biology

Technical Elective LIST C: SOFTWARE ENGINEERING BASIC SCIENCE ELECTIVES Structure, molecular composition and function in sub-cellular and cellular systems. Three hours (lectures, web modules), one lab (two hours); one term Prerequisite(s): One of Grade 12 Biology U, BIOLOGY 1P03 or registration in an Engineering program Co-requisite(s): WHMIS 1A00, and BIOSAFE 1BS0 (or HTHSCI 1BS0) if not already completed. Both requirements must be completed prior to the first lab. Not open to students with credit or registration in HTHSCI 1I06 A/B or ISCI 1A24 A/B. Students are strongly encouraged to take BIOLOGY 1A03 and BIOLOGY 1M03 in the different terms.

BIOLOGY 1M03

Biodiversity, Evolution and Humanity

Technical Elective LIST C: SOFTWARE ENGINEERING BASIC SCIENCE ELECTIVES Fundamental evolutionary and ecological concepts with particular reference to the diversity of life. Three lectures, seminar/lab (two hours every other week); one term Prerequisite(s): Grade 12 Biology U or BIOLOGY 1P03 Not open to students with credit or registration in ISCI 1A24 A/B. Students are strongly encouraged to take BIOLOGY 1A03 and 1M03 in the different terms.

CHEM 1AA3

Introductory Chemistry II

Technical Elective LIST C: SOFTWARE ENGINEERING BASIC SCIENCE ELECTIVES A discussion of organic chemistry, chemical kinetics, acid-base equilibrium, and the energetics of phase transformations, with emphasis on relevant experimental techniques and solving real problems ranging from drug discovery to environmental chemistry.

COMPENG 3DQ5

Digital Systems Design

Technical Elective LIST B: MECHATRONICS Permission of ECE required

COMPENG 4DN4

Advanced Internet Communications

Technical Elective LIST B: MECHATRONICS 4 units Advanced internet protocols; routing, security, encryption; quality of service; ATM, RSVP, video and voice over IP; terminals, gateways and gatekeepers; wireless networks; WDM systems; optical crossconnects. Three lectures, one tutorial, one lab every other week; second term Prerequisite(s): COMPENG 4DK4

COMPENG 4DS4

Embedded Systems

Technical Elective LIST B: MECHATRONICS Embedded processor architectures and SOC organization; EDA tools for hardware/software co-design; co-verification and testability; interfacing; co-processors, soft processors and ASIP design; real-time systems; applications. Two lectures, one tutorial, one lab every week; second term Prerequisite(s): COMPENG 3DQ5, or permission of the Department

COMPENG 4TN4

Image Processing

Technical Elective LIST B: MECHATRONICS Digital image formation and representation; filtering, enhancement and restoration; edge detection; discrete image transforms; encoding and compression; segmentation; recognition and interpretation; 3D imagery; applications. Three lectures, one tutorial, one lab every other week; second term Prerequisite(s): ELECENG 3TP4 or 3TP3; one of ELECENG 3TQ4, ELECENG 3TQ3 or STATS 3Y03

COMPSCI 3AC3

Algorithms and Complexity

Undergraduate LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES Basic computability models; the Church-Turing thesis, complexity classes; P versus NP; NP-completeness, reduction techniques; algorithmic design strategies; flows, distributed algorithms, advanced techniques such as randomization. Three lectures, one tutorial (one hour), second term Prerequisite(s): COMPSCI 2C03 or SFWRENG 2C03, COMPSCI 2AC3 or 2FA3 or SFWRENG 2FA3

COMPSCI 3DM3

Introduction to Data Mining

Undergraduate LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES This course introduces the core techniques in Big Data analytics, also known as knowledge discovery and data mining. Topics covered by this course include: frequent pattern mining, classification and clustering. Assignments and mini programming projects will be used to enhance and evaluate the learning performance of students. 3 lectures, 1 tutorial (1hour) PREREQUISITE(S): – One of COMPSCI 2DB3, COMPSCI 3DB3, SFWRENG 3DB3; – One of COMPSCI 2C03, SFWRENG 2C03 SFWRENG 2MD3, MECHTRON 2MD3; – One of COMPSCI 2ME3, SFWRENG 2AA4, SFWRENG 3K04, MECHTRON 3K04; – One of STATS 1L03, STATS 2D03, STATS 3Y03.

COMPSCI 3EA3

Software Specifications and Correctness

Undergraduate LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES Formal specifications in software and system development; validation; verification; presentation of information; practical experience in formal specification and tool-supported verification. Three lectures; one tutorial (one hour); one term Prerequisite(s): COMPSCI 2LC3 or 2DM3, 2AC3 or 2FA3, 2ME3, 2SD3 or 3SD3 Offered on an irregular basis.

COMPSCI 3IS3

Information Security

Undergraduate LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES Basic principles of information security; threats and defences; cryptography; introduction to network security and security management. Three lectures; one term Prerequisite(s): COMPSCI 2AC3 or 2FA3 or SFWRENG 2FA3, and COMPSCI 2C03 or SFWRENG 2C03 Offered on an irregular basis.

COMPSCI 4AD3

Advanced Databases

Undergraduate LIST D: SOFTWARE ENGINEERING AND SOCIETY TECHNICAL ELECTIVES Advanced topics in database systems technology and design. Topics include: query processing; query optimization; data storage; indexing; crash recovery; physical database design; introductory data mining techniques. Three lectures, one tutorial; one term Prerequisite(s): COMPSCI 3DB3 Antirequisite(s): SFWRENG 4AD3 Cross-list(s): SFWRENG 4AD3 Offered on an irregular basis.

COMPSCI 4DC3

Distributed Computing

Undergraduate LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES Models of distributed computation, formal reasoning about distributed systems, time and message complexity, distributed agreement under adversarial attacks, distributed coordination and symmetry breaking, peer-to-peer computing, simulation as a tool for building more advanced functionality, actor-model programming. Three lectures, one tutorial; one term Prerequisite(s): One of COMPSCI 2C03 or SFWRENG 2C03 or SFWRENG 2MD3, and one of COMPSCI 2SD3 or 3SD3 or SFWRENG 3BB4 or SFWRENG 3SH3 Offered on an irregular basis.

COMPSCI 4ML3

Introduction to Machine Learning

Undergraduate LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES Regression, Classification and Decision Theory, Bias-Variance Trade-off, Linear Models, Kernel Methods, Probabilistic Models, Neural Networks, Model Aggregation, Unsupervised Learning. Three lectures, one tutorial; one term Prerequisite(s): One of COMPSCI 2C03 or SFWRENG 2C03 or SFWRENG 2MD3. One of STATS 1L03, STATS 2D03, STATS 3Y03. One of COMPSCI 4O03 or 4X03 or SFWRENG 3O03 or 4X03 is recommended. Offered on an irregular basis.

COMPSCI 4WW3

Web Systems and Web Computing

Undergraduate LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES Network protocols underlying the world wide web; client-side programming: markup, styles, scripts, design, mobile/desktop; server-side programming: databases, dynamic languages; web services; cloud technologies; security. Three lectures; one term Prerequisite(s): COMPSCI 2ME3 or SFWRENG 2AA4; completion of COMPSCI 2DB3 or 3DB3, 3IS3, or 3N03 or 4C03 is recommended. Offered on an irregular basis.

COMPSCI 6O03

Linear Optimization

Graduate Linear programming, integer programming, decision trees, network flow problems, graph algorithms, route planning, applications to engineering problems.

COMPSCI 6TB3

Syntax Based Tools and Compilers

Graduate Lexical analysis, syntax analysis, type checking; syntax-directed translation, attribute grammars; compiler structure; implications of computer architecture; mapping of programming language concepts; code generation and optimization.

ELECENG 3PI4

Energy Conversion

Technical Elective LIST B: MECHATRONICS Permission of ECE required.

ELECENG 4BC3 / IBEHS 4BC3

Modelling of Biological Systems

Technical Elective LIST B: MECHATRONICS Introduction to mathematical and engineering methods for describing and predicting the behaviour of biological systems; including sensory receptors, neuromuscular and biomechanical systems; statistical models of biological function; kinetic models of biological thermodynamics. Prerequisite(s): Registration in Level IV Electrical and Biomedical Engineering

ELECENG 4BD4 / IBEHS 4BD4

Biomedical Instrumentation

Technical Elective LIST B: MECHATRONICS Permission of ECE required.

ELECENG 4OJ4

Research Project

Technical Elective LIST B: MECHATRONICS A research-oriented project under the direct supervision of a faculty member to foster initiative and independent creativity while working on an advanced topic.First or second term Prerequisite(s): Prior arrangement with an Electrical and Computer Engineering faculty member, a minimum cumulative GPA of 9.5, registration in Level IV or V of any program in the Department of Electrical and Computer Engineering; or permission of the department. Antirequisite(s): COMPENG 4OK4, ELECENG 4OK4, IBEHS 3I06 A/B

ELECENG 4PN4

Electric Motor Drives

Technical Elective Fundamentals of electric motor drives are studied. The operating principles of different electric motor types and drives, speed and position control, starting, and braking are covered. Three lectures, one tutorial, one lab every other week; second term Prerequisite(s): ELECENG 3PI4

ENGINEER 4EX3 A/B

Experiential Engineering Design

Technical Elective LIST B: MECHATRONICS

ENGPHYS 3O04

Introduction to Fluid Mechanics and Heat Transfer

Technical Elective LIST B: MECHATRONICS Fluid properties and statics are introduced. Basic equations of continuity, energy and momentum for internal and external flows are discussed. Similitude, dimensional analysis, measuring devices, fluid machinery and hydraulic networks. Conduction and convection heat transfer. Three lectures, one lab (three hours each) every other week; one tutorial, second term Prerequisite(s): MATH 2Z03 and credit or registration in MATH 2ZZ3 Antirequisite(s): CIVENG 2O04, MECHENG 3O04, CHEMENG 2O04

ENGPHYS 4B03

Biosensors – Fundamentals and Applications

Technical Elective This course covers the underlying operating principles and defining metrics of biological sensors, and it will discuss the integration of these sensors into systems for diagnostics and health monitoring applications. Three lectures; first term Prerequisite(s): Registration in Level III or above in any engineering program or registration in Level IV or above in the Integrated Biomedical Engineering & Health Sciences (IBEHS) Program.

ENGPHYS 4I03

Introduction to Biophotonics

Technical Elective This course covers the basic principles of light interaction with biological systems and specific biomedical applications of photonics such as optical light microscopy, endoscopic imaging, spectroscopy in clinical diagnosis, flow cytometry, micro-optical sensors, etc. Three lectures; second term Prerequisite(s): Registration in Level III or above in a Faculties of Engineering, Science, or Health Sciences, or the Integrated Biomedical Engineering & Health Sciences (IBEHS) Program Cross-list(s): MEDPHYS 4I03

ENGPHYS 4QC3

Introduction to Quantum Computing

Technical Elective LIST B: MECHATRONICS An introduction to quantum computing including qubits, entanglement, quantum key cryptography, teleportation, quantum circuits and algorithms, spin qubits. Three lectures; second term Prerequisite(s): ENGPHYS 2QM3 or PHYSICS 2C03

ENVIRSC 1C03

Climate, Water And Environment

Technical Elective LIST C: SOFTWARE ENGINEERING BASIC SCIENCE ELECTIVES An introduction to the science of environmental issues and sustainability through the study of the soil, climate and water processes.

ENVIRSC 1G03

Earth and the Environment

Technical Elective LIST C: SOFTWARE ENGINEERING BASIC SCIENCE ELECTIVES An introduction to environmental geology and geomorphology through study of the processes that form the earth and its surface features. A mandatory field trip will be held.

HTHSCI 1I06 A/B

Cellular and Molecular Biology

Technical Elective Students will explore the molecular basis of cellular communication (gene expression, cellular signaling) underlying disease processes. A hybrid approach blending didactic and inquiry-based approaches will be used. Two sessions per week (three hours each); two terms Prerequisite(s): Grade 12 U Biology and registration in Health Sciences I, or Grade 12 U Biology and registration in the Integrated Biomedical Engineering and Health Sciences (IBEHS) program. Co-requisite(s): WHMIS 1A00 . Students registering in HTHSCI 1I06 A/B must also register in WHMIS 1A00 when completing their registration. Antirequisite(s): BIOLOGY 1A03

HTHSCI 2E03

Inquiry II: Biochemistry

Technical Elective LIST C: SOFTWARE ENGINEERING BASIC SCIENCE ELECTIVES This course will use an inquiry based format to introduce key concepts in biochemistry, molecular biology and biomedical sciences to understand illnesses such as infectious diseases, metabolic disorders, genetic diseases and cancer. One term Prerequisite(s): HTHSCI 1I06 A/B

MATLS 3M03

Mechanical Behaviour of Materials

Technical Elective LIST B: MECHATRONICS

MECHENG 4AA3

Aerodynamics

Technical Elective Forces and moments associated with flow around airfoils and bodies. Finite wings. Potential flow and introduction to panel methods. Thin airfoil theory and symmetric and cambered airfoils. Introduction to aircraft stability and aeroelasticity. Three lectures; second term Prerequisite(s): MECHENG 3O04

MECHENG 4B03

Topics in Product Development

Undergraduate LIST B: MECHATRONICS Case studies using modern product development methods, value engineering, product specification, rapid product development, lean design and continuous improvement. Product liability and robust design. Three lectures, one tutorial; first term Prerequisite(s): Registration in Level IV or above of any Mechanical Engineering or Mechatronics Engineering program

MECHENG 4E03

Microelectromechanical Systems (MEMS)

Technical Elective LIST B: MECHATRONICS Permission of Mechanical Engineering required.

MECHENG 4O04

Sustainable Energy Systems

Technical Elective Assessment of current and future energy systems, covering resources, extraction, conversion with emphasis on meeting regional and global energy needs in a sustainable manner. Different renewable and conventional energy technologies and their attributes. Evaluation and analysis of energy technology systems in the context of political, social, economic and environmental goals. Four lectures; second term Prerequisite(s): MECHENG 2W04, 3O04; or ENGPHYS 2NE3, 3O04; or permission of the Department

MECHENG 4Q03

Mechanical Vibrations

Technical Elective LIST B: MECHATRONICS Transient and steady state vibration of single- and multi-degree of freedom systems. Free and forced vibrations of single and multiple degree-of-freedom mechanical systems, transient response, damping and vibration isolation. Three lectures; first term Prerequisite(s): ENGINEER 2Q04 or MECHENG 2Q04 or 2QA4 and registration in any Mechanical Engineering or Mechatronics program

MECHENG 4Z03

CAD/CAM/CAE

Technical Elective LIST B: MECHATRONICS Solid modelling theory, part creation, assemblies and rigid bodies, mechanism simulation, B-Splines, data exchange, CNC machining and inspection. Major project using computer laboratory facilities. Three lectures, one lab (one hour); second term Prerequisite(s): Registration in Level IV or above of any Mechanical Engineering or Mechatronics Engineering program Antirequisite(s): MECHENG 4ZR3

MECHTRON 4AX3

Predictive and Intelligent Control

Undergraduate LIST A: MECHATRONICS, LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES This course introduces several concepts used in systems engineering, predictive control and artificial intelligence. A variety of techniques including prediction and estimation, linear models, basic optimization techniques, Monte Carlo techniques, neural networks, and clustering are introduced. The techniques are applied to predictive and smart systems by the example of model predictive control and intelligent control, classification and decision-making. The course is intended for engineering students with understanding in signals and systems and control. Three lectures and one tutorial; one term Prerequisite(s): MECHTRON 3DX4 or SFWRENG 3DX4 or IBEHS 4A03 Offered on an irregular basis.

PHYSICS 1L03

Physics Of Living Systems

Technical Elective LIST C: SOFTWARE ENGINEERING BASIC SCIENCE ELECTIVES

SFWRENG 3DB3

Databases

Undergraduate LIST A: MECHATRONICS Data modeling, integrity constraints, principles and design of relational databases, relational algebra, SQL, query processing, transactions, concurrency control, recovery, security and data storage.

SFWRENG 3FP3

Functional Programming

Undergraduate LIST D: SOFTWARE ENGINEERING AND SOCIETY TECHNICAL ELECTIVES, LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES Functional programming; lists and algebraic data types, pattern matching, parametric polymorphism, higher-order functions, reasoning about programs; lazy and strict evaluation; programming with monads; domain-specific languages.

SFWRENG 3GB3

Game Design

Undergraduate LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES, LIST G: COMPUTER SCIENCE Game concepts. Creative and expressive play. Storytelling and narratives. User interfaces for games. Gameplay. Core mechanics. Game Balancing. Software architecture of games. Level design. Genres. Physics Engines.

SFWRENG 3GC3

Computer Graphics

Undergraduate LIST D: SOFTWARE ENGINEERING AND SOCIETY TECHNICAL ELECTIVES, LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES Mathematical foundations, the graphics pipeline, geometrical transformations, 3D visualization, clipping, illumination and shading models and the impact of graphics on society.

SFWRENG 3MD4

Safe Software-Intensive Medical Devices

Undergraduate LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES, IBEHS TECHNICAL ELECTIVES Comprehensive overview of and experience with system development and assurance for safety critical software-intensive systems in general, and safe, secure and effective medical devices in particular: System requirements, validation, system design including hardware and software components, software design, implementation, and verification. Three lectures, one lab (two hours); one term Prerequisite(s): COMPENG 2SI4 or COMPSCI 2C03 or SFWRENG 2C03 or 2MD3

SFWRENG 3MX3

Signals and Systems

Undergraduate LIST G: COMPUTER SCIENCE Linear systems, signals, filters; time and frequency domains; single input-single output systems; discrete and continuous time; sampling theorem; Fourier series; Fourier, Laplace, and z transforms; stability.

SFWRENG 3RA3

Software Requirements And Security Considerations

Undergraduate LIST A: MECHATRONICS Software requirements gathering. Critical systems requirements gathering. Security requirements. Traceability of requirements. Verification, validation, and documentation techniques. Software requirements quality attributes. Security policies. Measures for data confidentiality. Design principles that enhance security. Access control mechanisms.

SFWRENG 3S03

Software Testing

Undergraduate LIST G: COMPUTER SCIENCE Measurements. Unit testing, slicing and debugging, integration testing, regression testing, testing strategies, test coverage.

SFWRENG 3SH3

Operating Systems

Undergraduate LIST D: SOFTWARE ENGINEERING AND SOCIETY TECHNICAL ELECTIVES, LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES Processes and threads, synchronization and communication; scheduling, memory management; file systems; resource protection; structure of operating systems.

SFWRENG 4AD3

Advanced Databases

Undergraduate LIST D: SOFTWARE ENGINEERING AND SOCIETY TECHNICAL ELECTIVES, LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES Advanced topics in database systems technology and design. Topics include: query processing; query optimization; data storage; indexing; crash recovery; physical database design; introductory data mining techniques.

SFWRENG 4C03

Computer Networks And Security

Undergraduate LIST A: MECHATRONICS Physical networks, TCP/IP protocols, switching methods, network layering and components, network services. Information security, computer and network security threats, defense mechanisms, encryption.

SFWRENG 4E03

Performance Analysis Of Computer Systems

Undergraduate LIST A: MECHATRONICS, LIST F: ADDITIONAL TECHNICAL ELECTIVES FOR SOFTWARE ENGINEERING AND EMBEDDED SYSTEMS OR GAME DESIGN Use of queuing models and simulation to predict computer system performance and find bottlenecks in a system. Types of models, distributions. Markov models. Modelling storage and network behaviour, locks, critical sections, concurrency. Introduction to analytical system reliability.

SFWRENG 4F03

Parallel Computing

Undergraduate LIST A: MECHATRONICS, LIST D: SOFTWARE ENGINEERING AND SOCIETY TECHNICAL ELECTIVES, LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES Parallel architectures, design and analysis of parallel algorithms; distributed-memory, shared-memory and GPU computing; communication cost, scalability; MPI, OpenMP and OpenACC; tuning parallel programs for performance.

SFWRENG 4J03

Communications Systems

Undergraduate LIST A: MECHATRONICS, LIST D: SOFTWARE ENGINEERING AND SOCIETY TECHNICAL ELECTIVES, LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES, LIST G: COMPUTER SCIENCE Fundamental communications concepts: information, entropy, channel capacity, codes, data compression, adaptive channel equalizers, modulation/demodulation of signals, tracking, Kalman filtering, use of specialized signal processing hardware. Software in communication systems.

SFWRENG 4TE3

Continuous Optimization Algorithms

Undergraduate LIST A: MECHATRONICS, LIST D: SOFTWARE ENGINEERING AND SOCIETY TECHNICAL ELECTIVES, LIST E: SOFTWARE ENGINEERING TECHNICAL ELECTIVES, LIST F: ADDITIONAL TECHNICAL ELECTIVES FOR SOFTWARE ENGINEERING AND EMBEDDED SYSTEMS OR GAME DESIGN, IBEHS TECHNICAL ELECTIVES Fundamental algorithms and general duality concepts of continuous optimization. Special attention will be paid to the applicability of the algorithms, their information requirements and computational costs. Practical engineering problems will illustrate the power of continuous optimization techniques.