An introduction to the practice of management engineering, including topics such as criteria-based decision making with a focus on efficiency and effectiveness; cause and effect analysis, and an engineering approach to problem solving; flow and process analysis; teamwork and project management; decision-making tools; and written and verbal communication. Engineering design methods are also introduced, including a design project with small groups, as are aspects of the engineering profession including topics such as ethics, safety, and legal liability. Professional development for preparation for co-op terms is also included.
MSE 121Introduction to Computer Programming0.50 units
An introduction to computer programming using a high level programming language. Concepts and topics covered include the basic components of algorithms (primitive operations, variables, sequencing operations, conditionals/branching, repetition/loops, subroutines/functions), problem decomposition, abstraction, testing and debugging, pseudo-code, file based input and output, use of a modern development environment including a symbolic debugger, good coding style, pointers/references, and basic data structures (arrays, records, objects).
MSE 131Work Design and Facilities Planning0.50 units
The course introduces fundamental concepts in two main areas: The first is work analysis and design where work methods design, motion and time study, and work sampling are covered. The second covers basic concepts in facilities planning such as process analysis, flow design, facility location and layout, and material handling systems. Students will apply these concepts in design activities in labs and projects.
Introduction to the concepts of learning, person perception, attitudes, and motivation in an organization. Consideration of communication, roles, norms, and decision making within a group. Discussion of power, control, leadership, and management in light of the above concepts.
Antirequisites
Complete all of the following
Not completed nor concurrently enrolled in any of the following:
AFM280 - Introduction to Organizational Behaviour (0.50)
This course uses a quantitative approach to problem solving using mathematical modelling, solution by solver, and output and sensitivity analysis. Students learn how to analyze and solve decision problems in Management and Engineering systems following the Engineering process: understanding the problem, identifying appropriate models and solution methods, formulating and structuring the model, and interpreting the results. The course covers linear, integer, and nonlinear, optimization modelling and dynamic programming.
Design and analysis of data structures and algorithms with an emphasis on further development of computer programming skills. Topics include algorithms for searching, sorting, stacks, queues, trees, and graphs. Comparison of algorithms on different data structures. Solutions to common engineering problems in computer science using algorithms and data structures. Introduction to mathematical analysis of space and time complexity with a focus on designing solutions that can scale to large input sizes.
Prerequisites
Complete all of the following
Complete 1 of the following
Must have completed the following:
MSE121 - Introduction to Computer Programming (0.50)
This course introduces students to software systems that use a relational database management system (RDBMS) for data storage. One focus of this course is multi-tier software architectures, such as websites and other software as a service (SaaS) systems. Students will learn common software concepts such as design patterns, and modelling processes, objects, logic, and data. Students will learn how to organize data in a RDBMS and how to interact with the database using the structured query language (SQL).
A first of a two-course sequence that introduces fundamental concepts in probability and statistics. It covers probability concepts, random variables, graphical display of distributions and data, discrete and continuous probability distributions, sampling, estimation, confidence intervals, experimental design, hypothesis testing, and simple linear regression and correlation. Students learn how to graphically explore data, conduct, and analyze a two-treatment experiment, and model data with linear regression, and interpret its fit. Students learn to use statistical computing software (e.g., R) to perform data analyses. Emphasis is placed on gaining experience with data collected from student-conducted experiments.
The second of a two-course sequence that introduces probability and statistics. It covers quantitative information displays, conditional probability and Bayes' rule, transforms, joint distributions, special discrete and continuous distributions (t, F, chi-square, Poisson), fitting distributions to data, maximum likelihood estimation, multiple regression, experimental design (blocking, factorial), paired hypothesis tests, analysis of variance, non-parametric statistics, and computer intensive statistics (bootstrap). In addition, students learn how to clean data, handle missing values, smooth data, and perform the statistical techniques covered in the course using a statistical computing package (e.g., R). Emphasis is placed on working with actual data collected from student experiments and other sources such as industrial partners.
MSE 261Engineering Economics: Financial Management for Engineers0.50 units
Introductory finance: time value of money, cash flow analysis. Investment evaluation methods: present worth, annual worth, and internal rate of return. Depreciation models and asset replacement analysis. The impact of inflation, taxation, uncertainty, and risk on investment decisions.
This course introduces students to key concepts in microeconomics, with an emphasis on applications to managerial decision-making. Topics include basic analysis of supply and demand, demand functions and the theory of consumer behaviour, production and costs, market equilibrium, competition between industry participants, and pricing strategies of firms under different market structures.
Antirequisites
Not completed nor concurrently enrolled in any of the following:
MSE 271Advanced Calculus and Numerical Methods0.50 units
This course introduces students to first and second order ordinary differential equations, vector calculus, and numerical methods for solution of systems of equations, and ordinary differential equations. Applications in management engineering are emphasized.
This course provides a survey of engineering design theories, methods, and tools as they pertain to need finding, problem formulation, and solution generation and evaluation. Students learn about different approaches to design project and team management and communication, as well as the relationship between design and environmental, social, and economic sustainability. Students gain experience in the entire design cycle by working on a number of small design problems throughout the term. Students form teams and work on a term-long project centred on need finding and problem formulation. This activity is expected to result in a project topic that can be further developed in the capstone design series of courses (MSE 401/402).
MSE 311Organizational Design and Technology0.50 units
The focus of this course is on the procedures and variables involved in the design and redesign of organizations. Issues such as departmentation, differentiation, integration, internal politics, innovation, authority, and control are discussed in the context of the underlying technology of the organization. Emphasis will be placed on how one designs both the technical and the organizational systems to ensure their compatibility, noting the effects that one has on the other.
This first course in optimization uses a quantitative approach to problem solving involving, mathematical modelling and formulations, solution methods, and output analysis. Students are introduced to a variety of practical problem formulations in management and engineering, a number of solution methods, including, but not limited to, linear optimization, network models, project management, and decision analysis. Students are also involved in a group project, where they go through conceptual and operational model design, analytical solution, output analysis, and recommendation.
Antirequisites
Complete all of the following
Not completed nor concurrently enrolled in any of the following:
BME411 - Optimization and Numerical Methods (0.50)
MSE 332Deterministic Optimization Models and Methods0.50 units
This course builds on the material presented in MSE 331, and explores more advanced optimization techniques and applications. Methods, such as integer optimization, dynamic programming, and heuristics, are introduced and used to design solution alternatives for applications from management engineering. This may include network and process design in logistics, transportation, telecommunications, and healthcare.
Prerequisites
Complete 1 of the following
Must have completed at least 1 of the following:
BME411 - Optimization and Numerical Methods (0.50)
This course introduces the use of discrete event simulation as an approach for understanding and analyzing complex management systems. Topics include an introduction to simulation modelling, general purpose and special purpose simulation languages, designing valid and credible simulation models, input data analysis, output analysis and experimental design.
MSE 334Operations Planning and Inventory Control0.50 units
This course exposes students to production planning and inventory control approaches in industrial and service systems. Production planning topics cover capacity and resources planning, production scheduling, manufacturing resource planning, just-in-time and lean manufacturing. Inventory control topics cover lot sizing policies, deterministic and stochastic inventory policies. The course involves a design project of a production and/or inventory system.
Prerequisites
Complete all of the following
Complete 1 of the following
Must have completed the following:
MSE131 - Work Design and Facilities Planning (0.50)
MSE 342Principles of Software Engineering0.50 units
In this course, students learn how to work as a team to efficiently design and build software that works correctly and solves a customer's problem. Topics include software development processes, requirements gathering and analysis, software design, specifications, estimation, scheduling, revision control, software testing, deployment, and team behaviour.
This course is designed to provide in-depth exposure to the concepts of human-computer interaction and methods of interactive information system design. The course will focus on techniques for building information systems that meet human needs and capabilities by following a system development lifecycle: user requirements analysis, information and interaction design, prototyping and evaluation.
A work-term report is a written report that provides an opportunity for students to effectively communicate, document, and reflect on engineering experience gained during a preceding work term. In the report, students draw connections between the theoretical aspects of engineering taught in the classroom and the practical applications of that theory in the workplace. Reports are due on the tenth day of lectures for the academic term in which the report is required.
A work-term report is a written report that provides an opportunity for students to effectively communicate, document, and reflect on engineering experience gained during a preceding work term. In the report, students draw connections between the theoretical aspects of engineering taught in the classroom and the practical applications of that theory in the workplace. Reports are due on the tenth day of lectures for the academic term in which the report is required.
MSE 401Management Engineering Design Project 10.50 units
Teams formed in MSE 302 conduct concept generation and detailed design iterations on the design problem formulated in MSE 302, or on a new customer-defined problem. Project progress is communicated and evaluated in periodic design reviews. Teams establish and maintain suitable project control and team processes.
MSE 402Management Engineering Design Project 20.50 units
Student teams continue working on the design project begun in MSE 302 and MSE 401. They complete design iterations, plan and perform verification and validation of the solution, and deliver a final implementation of the design. Project progress and final design are communicated and evaluated in periodic design reviews and at a public symposium. Teams maintain suitable project control and team processes.
This course will provide students with an overview of how management, psychology, marketing, and related fields have approached the topics of leadership, influence, and power. The first section of the course will address the antecedents of leadership (e.g., How do specific leaders emerge? What are the qualities of good leaders?). The second section of the course will address the act of leadership (e.g., How do leaders influence their followers? What limitations are inherent to leadership positions?) Specific topics covered include leadership styles, persuasion, social influence, evolutionary perspectives, motivating others, and managing conflict.
Antirequisites
Not completed nor concurrently enrolled in any of the following:
MSE 422Economic Impact of Technological Change and Entrepreneurship0.50 units
This course is designed to analyze the impact of technological change and entrepreneurship at a firm and societal level, primarily in terms of the economic antecedents and consequences of new technology. The scope of the course ranges from the study of the determination of productivity and its effect on economic growth to the determination of innovative activity and performance.
Prerequisites
Complete all of the following
Complete 1 of the following
Must have completed at least 1 of the following:
AE392 - Economics and Life Cycle Cost Analysis (0.50)
Introduction to operations research models and methods for problems with random, stochastic, and probabilistic components. Topics include birth and death processes, branching processes, waiting line models, and Markov decision processes. Applications include the design, modelling, and analysis of service and manufacturing systems, with emphasis on important functions such as queueing, inventory, reliability, equipment replacement, and maintenance.
Prerequisites
Complete all of the following
Complete 1 of the following
Must have completed at least 1 of the following:
BME411 - Optimization and Numerical Methods (0.50)
MSE 432Production and Service Operations Management0.50 units
Introduction to management, planning, and control decisions in manufacturing and service settings using quantitative approaches. Topic areas include production, inventory, distribution, quality control, facilities layout, and process design. Students are exposed to a number of examples and case studies, and work on a project that involves analysis and discussion of improved designs.
MSE 433Applications of Management Engineering0.50 units
This course exposes students to a variety of application areas in management engineering and introduces to them the challenges inherent in implementing new management engineering systems. Topics will be chosen from areas such as manufacturing, services, logistics, finance, healthcare, and engineering.
Prerequisites
Complete all of the following
Complete 1 of the following
Must have completed the following:
MSE332 - Deterministic Optimization Models and Methods (0.50)
This course focuses on the efficient use of material, information, physical and human capital resources in supply-demand networks consisting of suppliers, manufacturers, distributors, retailers and customers. It emphasizes analytic tools used to design, implement and sustain competitive supply chain systems. The material will highlight application of supply chain practices in industry and supply chain implementation challenges. Issues associated with international or global supply chains will be discussed.
Prerequisites
Complete all of the following
Complete 1 of the following
Must have completed at least 1 of the following:
MSE334 - Operations Planning and Inventory Control (0.50)
MSE432 - Production and Service Operations Management (0.50)
This course covers more advanced topics in optimization that go beyond the contents of MSE 232, MSE 331, and MSE 332. The course will cover topics such as constraint programming, stochastic programming, large scale optimization, or complementarity problems.
Prerequisites
Complete 1 of the following
Must have completed the following:
MSE332 - Deterministic Optimization Models and Methods (0.50)
This course provides an introduction to analysis, design, and implementation of decision support systems for engineering and business applications. Operations research modelling techniques and software are integrated with database systems and computer interfaces to create systems that aid managerial decision-making. This course also discusses challenges in designing and implementing decision support systems based on models drawn from Operations Research.
Prerequisites
Complete all of the following
Complete 1 of the following
Must have completed the following:
MSE332 - Deterministic Optimization Models and Methods (0.50)
Must have completed the following:
MSCI332
Complete 1 of the following
Must have completed at least 1 of the following:
CS348 - Introduction to Database Management (0.50)
MSE 442Impact of Information Systems on Organizations and Society0.50 units
This course is designed to familiarize the student with issues related to the impact of computer-based technologies on individual jobs, organizations, and broader societal level. Particular emphasis will be placed on critical examination of various issues including privacy, security, ethical concern, and professional responsibilities.
This course provides an introduction to machine learning, including supervised and unsupervised learning. Emphasis is placed on proper procedures for the training and testing of models. Topics covered may include data cleaning and transformation, overfitting and generalization, n-fold cross validation, regression, decision trees, neural networks, rule finding, and clustering. Students learn to apply machine learning methods to management engineering problems using common tools such as R and Python.
MSE 452Decision Making Under Uncertainty0.50 units
This course deals with normative, descriptive, and prescriptive theories and models of decision making under uncertainty. The course focuses on concepts such as risk measures, Bayes theorem, and basic and multi-attribute utility theories. The course uses these concepts to build analytical decision-making models considering the randomness and/or risk-attitude of the decision-makers. Various forms of decision analysis techniques will be covered and typically include, expected utility maximization, the value of information analysis, one/two-way sensitivity analysis, and sequential Bayesian inference. Practical uses and limitations of the models and techniques will be illustrated.
Technical entrepreneurship is examined considering the role of independent business, entrepreneurial behaviour, types of business and enterprises, business structure, sources of venture concepts and capital, company operation and control, and business start up.
A work-term report is a written report that provides an opportunity for students to effectively communicate, document, and reflect on engineering experience gained during a preceding work term. In the report, students draw connections between the theoretical aspects of engineering taught in the classroom and the practical applications of that theory in the workplace. Reports are due on the tenth day of lectures for the academic term in which the report is required.
MSE 531Stochastic Processes and Decision Making0.50 units
This course builds on the material covered in MSE 431. Students will learn how to construct and analyze a range of stochastic decision models that are useful in the design and control of a wide variety of systems. Applications areas include the design of inventory control systems, telecommunication networks, healthcare polices, manufacturing control, and reliability analysis. Topics include Renewal-Reward Processes, Markov Decision Processes, Matrix Analytic Methods with application areas noted above.
This course provides an opportunity for students to learn the engineering behind search engines and how to optimize search engines to provide higher quality user experiences. This course focuses on text retrieval and web search. Topics include design and construction of retrieval systems, retrieval models, and evaluation of search engines.
This course provides students with an in-depth understanding of methods for evaluating the user experience on a large scale. Students will learn how to design user experiments that involve the collection and analysis of large quantities of data online, apply useful metrics for evaluating the user experience, and use this analysis to inform their designs of software and technology.
This course provides a deeper understanding of machine learning (ML) techniques by utilizing students' prior background in ML and operations research to understand the drivers of ML methodologies rather than using black-box processes. The course first reviews supervised and unsupervised learning methods, and then dives deeper into their assumptions, mathematical models, and underlying algorithms to help students systematically develop and enhance ML processes. Using the same approach, the course covers more advanced topics in ML, such as neural networks and reinforcement learning. Application areas within this course may include, but are not limited to healthcare, energy, sports, transportation, and manufacturing.
Prerequisites
Complete all of the following
Complete 1 of the following
Must have completed the following:
MSE332 - Deterministic Optimization Models and Methods (0.50)
The course focuses on the analysis, evaluation, and improvement of quality based on statistical tools. Topics include process capability analysis, statistical process control, experimental design and the Taguchi method, and acceptance sampling. The emphasis is on the assessment of quality and the design of alternate processes and/or quality assessment schemes to improve quality.
Scheduling is the sequencing of tasks to scarce resources. By exploring scheduling problems found in industry, this course will discuss scheduling framework and notation as well as algorithmic, heuristic, and mathematical programming solution approaches. Students will be introduced to the theoretical background in these areas, but the emphasis will be placed on modelling and solving scheduling problems in practice. Students will apply these concepts in design activities in assignments and a course project.
Prerequisites
Complete 1 of the following
Must have completed at least 1 of the following:
BME411 - Optimization and Numerical Methods (0.50)
MSE 597Complementary Studies Topics in Management Science and Engineering0.50 units
A complementary studies course on advanced topics in management science and engineering will be offered when resources are available. For current offerings, see the Course Selection Offerings List or the Schedule of Classes.
MSE 598Special Topics in Management Engineering0.50 units
A course on advanced topics in management engineering will be offered when resources are available. For current offerings, see the Course Selection Offerings List or the Schedule of Classes.
MSE 601Research Methods in the Management Sciences0.50 units
This course focuses on methods used in empirical research in the management sciences. It encompasses: stages in the research process, theory building, problem definition, research strategies and designs, measurement issues, sampling, ethical concerns, data analysis, and the communication of research results. These issues will be examined in published research and student proposals. Priority may be given to Management Sciences students.
MSE 602Strategic Management of Technological Innovation0.50 units
This course includes: integrating technology and business strategy; design and evolution of technology strategy; development of the firm's innovative capabilities; creating and implementing systems for innovation; innovation challenges in established firms. In addition to a textbook, cases are used to add realism and context to this course. Priority may be given to Management Sciences students.
MSE 603Principles of Operations Research0.50 units
This course surveys a spectrum of models and techniques in Operations Research, with emphasis on applications. It focuses on the development of modeling skills, the interpretation of results, sensitivity analysis and computer implementations of decision support systems. Topics include linear, integer and network optimization models. Simulation analysis and other topics in stochastic processes may also be covered. The use of quantitative models in different levels of the decision making hierarchy are illustrated through case studies and readings from the Management Sciences literature. Priority may be given to Management Sciences students.
Antirequisites
Not completed nor concurrently enrolled in any of the following:
MSE634 - Deterministic Models in Operations Research (0.50)
Introduction to the concepts of learning, person perception, attitudes, and motivation in an organization. Consideration of communication, roles, norms, and decision making within a group. Discussion of power, control, leadership, and management in light of the above concepts. Priority may be given to Management Sciences students.
The course provides a comprehensive background in the management principles needed to effectively enhance interpersonal skills, evaluate organizational performance and apply organizational functioning. The subject areas that make up this course, in order to provide this broad background, include: Financial Accounting, Management Accounting, Organizational Behaviour, Management, Information Systems, Production and Operations Management, and Marketing. Key objectives of the course include (1) to enable confident interactions with functional specialists, (2) to provide tools for the evaluation of organizational performance, and (3) to enhance appreciation for the contributions, and applications of management theories to organizations. Priority may be given to Management Sciences students.
This course will examine economic concepts that are useful to management, from decisions about proposed investments in process changes or product modifications, to strategic considerations for the firm. Topics will include: techniques for financial evaluation of proposed investments; incorporating risk into evaluations; basic concepts from game theory; theory of demand; production functions; cost functions; competitive markets; other market structures. Priority may be given to Management Sciences students.
MSE 609Quantitative Data Analysis for Management Sciences0.50 units
Descriptive statistics and probability concepts; discrete and continuous probability distributions; sampling methods and the central limit theorem; estimation and confidence intervals; inference and hypothesis testing; linear regression and correlation; multiple regression and model building.
This course provides an introduction on health analytics including such topics as data acquisition, modelling, and predictive analytics. The course focuses on the practical application of the concepts to improve the quality of the analyses often found in the health sector. Application areas will be concentrated on topics found in health systems and may include topics such as planning and scheduling, disease diagnosis, and treatment planning. The learning outcomes include the ability to identify and apply appropriate analytical methods and models for healthcare.
MSE 620Organizations & Technical Systems0.50 units
This research seminar concentrates on a macro view of organizations as dynamic systems. It emphasizes the principles of effective management of organizations and technology. Further, the course examines the conceptual foundations of organizational theory and design. Priority may be given to Management Sciences students.
This course provides an introduction to the field of machine learning, with an emphasis on tools and algorithms that learn patterns from data. Topics covered may include data preparation, descriptive learning such as clustering, and predictive learning using classical methods such as regression and data-intensive methods such as deep learning. Students will read and present papers and complete a research project.
Antirequisites
Complete all of the following
Not completed nor concurrently enrolled in any of the following:
This course concentrates on the theoretical and practical issues related to the design of the human-computer interfaces. Aspects of human perception, cognition and various models of task analysis are discussed. Further, the course examines the principles of interface design and the related empirical evidence. Priority may be given to Management Sciences students
Antirequisites
Complete all of the following
Not completed nor concurrently enrolled in any of the following:
MSE 631Probabilistic Models in Operations Research0.50 units
The goal of this course is to enable students to think probabilistically. The modelling and analysis of uncertain systems in operations research is emphasized. Tools include renewal theory, Markov processes and queuing analysis, while application areas include production and inventory control, health-management, transportation, and other problems in probabilistic operations research. Priority may be given to Management Sciences students.
This course provides an introduction to Discrete Event Simulation. Topics covered include applications of discrete event simulation, simulation languages, data collection and input analysis, random number generation, validation, output analysis for a single system, comparison of several systems, variance reduction techniques and experimental design. Through a project, students will acquire the skills necessary to define a problem, develop and validate a conceptual and computer model, analyse the problem, and make recommendations. Priority may be given to Management Sciences students.
MSE 633Production and Inventory Management0.50 units
The course emphasizes inventory control models with deterministic and stochastic demand, and supply chain management. Other areas which might be addressed are aggregate planning, machine scheduling, material requirements planning, and multi-echelon production and distribution systems. Priority may be given to Management Sciences students.
MSE 634Deterministic Models in Operations Research0.50 units
The objective of this course is to provide students with an in-depth understanding of the theory and algorithms in deterministic optimization. Specifically, it covers advanced topics in linear optimization including simplex method, duality, sensitivity analysis, and interior point methods. Then, topics in integer optimization including polyhedral theory, branch-and-bound, and cutting plane algorithm are discussed. Other topics such as nonlinear optimization and dynamic programming may be covered.
Antirequisites
Complete all of the following
Not completed nor concurrently enrolled in any of the following:
MSE 638Information Systems Analysis and Design0.50 units
This course presents the foundations which underlie the development of management information systems. Emphasis is placed on the concepts, strategies, techniques and tools for identifying and specifying information systems requirements, and developing designs. Students are expected to complete an analysis and design project. Priority may be given to Management Sciences students.
With the rapid growth of unstructured natural language data, such as web pages, blogs, product reviews, news articles and enterprise data, there is an increasing need for systems that would retrieve relevant documents, extract specific information from them, mine opinions, summarize and categorize texts. This course provides students with an understanding of the major methods for retrieving, mining and analyzing textual data, with the emphasis on algorithms, techniques and their evaluation.
The course is concerned with the design, management and use of databases. The course combines theoretical foundations of database organization and database design methodologies with the practical aspects of developing, implementing and managing databases. Some topics include: relational database design, entity modelling, SQL, and comparison of different types of databases.
This course will provide students with an understanding of Project Management Fundamentals while allowing them to gain practical experience of International Project Management and Development in a live practical project. Topics covered include: Project Management Methodologies, Project Manager's Role, Managing Project Stakeholders, Scope, Quality and teams; Project Risk Management, Procurement, Leadership, and Ethics.
Antirequisites
Not completed nor concurrently enrolled in any of the following:
MSE 652International Business Management0.50 units
Companies today confront an increasing array of choices regarding markets, locations for key activities, organizational structures, and processes for managing across borders. This course provides students with the conceptual tools necessary to understand and work effectively in today's interconnected world by developing strategic perspectives that link the global environment and the capabilities and position of the firm. Topics include Globalization, International Strategy Development, Mode of Entry and Alliance Structures, Organizational Design, Structure and Control, Human Resources Management, Cross-cultural Issues, Ethics in International Business, International Marketing and Branding, International Operations, Exporting and Importing, and Global Corporate Sustainability.
MSE 682Organizational Strategy and Innovation0.50 units
This course examines how organizations formulate and execute strategies to drive innovation and sustain competitive advantage. Topics include linking organizational strategy with innovation processes, managing technology and change, building dynamic capabilities, and designing structures that foster creativity and collaboration. The course emphasizes how firms can adapt to technological disruption, coordinate innovation across functions, and align strategic priorities with long-term growth.
Antirequisites
Not completed nor concurrently enrolled in any of the following:
MSE602 - Strategic Management of Technological Innovation (0.50)
This course explores how data-driven analysis and modeling support effective decision-making in complex organizational settings. It emphasizes the formulation of analytical models, interpretation of results, and application of quantitative insights to real-world managerial problems. Topics include optimization, simulation, prescriptive analytics, and decision support under uncertainty. Students will develop practical skills in translating data into strategic and operational recommendations.
Antirequisites
Not completed nor concurrently enrolled in any of the following:
MSE 689Statistical Learning and Data Science0.50 units
This course introduces foundational concepts in statistics and data analysis for management and engineering applications. Topics include data visualization, regression, classification, and basic techniques in statistical learning. Students gain practical experience applying these methods to real data using examples from organizational and technological contexts.
Antirequisites
Not completed nor concurrently enrolled in any of the following:
MSE609 - Quantitative Data Analysis for Management Sciences (0.50)
MSE 702Linear Programming and Extensions0.50 units
Introduction to selected applications of LP. The simplex method. Duality and sensitivity analysis. Computer solutions to LP. Network flow problems with applications and algorithms. Special topics such as revised simplex method, primal-dual method, decomposition principle, generalized upperbounding and ellipsoid methods. Priority may be given to Management Sciences students.
The course focuses on the modeling and solution of practical optimization problems. It covers formulations based on integer and nonlinear optimization, solution approaches based on large-scale optimization, and algorithmic design and implementation. Topics include set covering formulations, Lagrangean relaxation, Benders decomposition, column generation, branch-and-price, nonlinear programming, and metaheuristics. Possible applications areas include bin packing, routing, scheduling, and logistics planning. Priority may be given to Management Sciences students.
MSE 709Logistics and Supply Chain Management0.50 units
Modern supply chain management encompasses the logistics of inventory and transportation flows, whether within a given organization or between that firm and other companies (suppliers, customers) that are part of its business. This course thus deal with models and analyses of the inbound transportation of raw materials, manufactured components and sub-assemblies. Another emphasis is the (outbound) physical distribution of finished goods from factory to consumer: freight transportation (various modes, customer service, multi-location inventory management and distribution-centre site selection. Specialized topics (for term projects) may be chosen from among Logistics Information Systems; Global Supply Chain Management; Vehicle Routing; or the Logistics of e-Commerce. Priority may be given to Management Sciences students.
MSE 712Decision Analysis Under Uncertainty0.50 units
The course goal is to understand, model and improve decision making under uncertainty and complexity. Bayesian principles and expected utility theory are combined, their underlying assumptions critically reviewed, and alternative theories surveyed. Other issues addressed include decision with multiple attributes. Priority may be given to Management Sciences students.
MSE 718Statistical Methods for Data Analytics0.50 units
The objective of this course is to develop skills with a range of procedures and programs for multivariate data analysis. The focus will be on practical issues such as selecting the appropriate analysis, preparing data for analysis, menu-driven and syntax programming, interpreting output, and presenting results of a complex nature.
This course covers predictive analytics that provides techniques to model the relationships between inputs and outcomes, and construct predictions about future outcomes, and prescriptive analytics that provides tools to optimize actions against a complex set of objectives to find best practices and design best policies under all circumstances. The theoretical techniques will be applied to supply chains, service industries, healthcare systems, revenue management, inventory management, and sports.
MSE 724Game Theory and Recent Applications0.50 units
Introduction to game theory including symmetric and asymmetric games, as well as static and dynamic games. Topics include game rules and information, mixed and continuous strategies, moral hazard, adverse selection, and introductory mechanism design. Applications such as: sustainability in supply chains, prediction markets, and contract design, are reviewed in this course.
MSE 731Matrix-Analytic Methods in Stochastic Models0.50 units
This course introduces matrix-analytic methods and shows their applications in queuing theory, inventory theory, supply chain management, telecommunications networks, reliability, finance mathematics, and risk and insurance analysis. In the first half of the course, the basic theory on phase-type distributions, Markovian arrival processes, and matrix-geometric solutions is introduced. In the second half of the course, applications of matrix-analytic methods in stochastic modeling (queuing, reliability, inventory, supply chain, etc.) are examined. Previous study of stochastic models is required, such as MSCI 631.
This course treats the broad subject of network models. Network flow problems form a special class of linear programming that arise in a wide variety of applications including transportation, telecommunications, logistics and supply chain management. The purpose is to study the properties of network flow models, to discuss extensions and various solutions approaches, and to survey some applications.
MSE 741Economics of Technological Change0.50 units
This is an applied course in industrial organization economics. It deals with productivity, the relationship between productivity and technological change, the determinants to firms' investments in research, development and innovation, the diffusion of innovations, entrepreneurship, and technology policy. Priority may be given to Management Sciences students.
Managing intellectual property (IP) effectively is crucial for sustaining competitive advantage and fostering growth. The course develops a deep understanding of the strategic dimensions associated with IP and the necessary analytical skills needed to support strategic decisions concerning IP. The course uses a hybrid approach using elements such as theoretical models and practical case studies. The course will cover various types of intellectual property, such as patents, trademarks, copyrights, and trade secrets, and topics such as IP protection, enforcement, commercialization, licensing agreements, and IP risk management. Previous study of economics (e.g., MSE 607) is recommended but not required.
This course is designed to provide the student with up-to-date understanding of the developments, issues and current research in the topics associated with knowledge as an asset in organizations. Topics include: knowledge and economic growth and change: the global knowledge-based economy; consequences of the increasing role of the knowledge worker; strategic and organizational roles of intellectual capital; monitoring, and valuing and reporting intellectual capital. Priority may be given to Management Sciences students.
This course introduces graduate students to theories, ideas, and findings in behavioural decision-making research. Although normative theories of judgment and decision-making will be discussed, the main focus of this course will be descriptive theories. The readings are selected to introduce students to a variety of issues dealing with judgment and decision-making in psychology and economics as well as other business disciplines such as marketing, finance, organizational behaviour and operations management. Possible topics will include decision-making under risk and ambiguity, emotions and decision-making, intuition vs. deliberation, and intertemporal choice.Priority may be given to Management Sciences students.
MSE 753Entrepreneurship and Intrapreneurship: Managing New Technology-based Firms0.50 units
An overview of the process of initiating startups, spin-outs or new ventures within an existing company. Ventures based on new technologies are a focus. Topics include extrpreneurship and organizational culture, opportunity identification and assessment, business plans and new venture diagnostics, protecting intellectual property, finance, marketing and the entrpreneurial team.