Summer Course Add/Drop Deadline: Some summer courses do not follow SGS add/drop deadlines since they are scheduled at unique dates. Please note the add/drop deadline in the course schedule below. If you would to add a course that is still within the course add deadline, please fill this form out with your signature. If you are having trouble dropping a course and it falls within the drop deadline, please use the same form. Please pass the form to d.duong@utoronto.ca for processing.
Leadership Courses Entrepreneurship & Innovation Courses Engineering & Society Courses
| FINANCE AND MANAGEMENT | |||||
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| Course Description *Click course title for syllabus link | Admin Info | Next Session Details | Fall 2025 | Winter 2026 | Summer 2026 |
| APS500H1: Negotiations in an Engineering Context | Not offered this year | ||||
| APS502H1: Financial Engineering | FALL 2025: Starts Sept 2, Tuesdays 12-3pm, in GB221 WINTER 2026: Starts Jan 5, Tuesdays 3-6pm, in SF3202 | x | x | ||
| APS1001H: Project Management | Course will be delivered Asynchronously | FALL 2025: Dec 9- Dec 19 WINTER 2026: Jan 5 - Mar 27 SUMMER 2026: ONLINE First-Subsection: May 4 - June 30 Course add deadline: May 11 Course drop deadline: June 1 Second-Subsection: July 2 - Aug 30 Course add deadline: July 6 Course drop deadline: July 27 | x | x | x |
| APS1004H: Human Resources Management: An Engineering Perspective | WINTER 2026: Jan 5 - March 30, Monday, 6-9pm in BA1230 SUMMER 2026: Aug 4 - Aug 17, Monday to Friday, daily 6-9pm, in BA1210. Course add deadline: Aug 5 Course drop deadline: Aug 10 | x | x | ||
| APS1005H: Operations Research for Engineering Management | Exclusion: MIE262 | SUMMER 2026: ONLINE Synchronous | July 27 - August 7th, 10-1pm Add Deadline: July 28 Drop Deadline: August 3 | x | ||
| APS1016H: Financial Management for Engineers | FALL 2025: Not offered in fall. SUMMER 2026: Not offered in summer | ||||
| APS1017H: Supply Chain Management and Logistics | To drop this course, please use course add/drop form, with your signature and submit to d.duong@utoronto.ca | SUMMER 2026: June 1 - June 12 Daily 10-1pm Course add deadline: June 2 Course drop deadline: June 5 | x | ||
| APS1020H: International Business for Engineers | SUMMER 2026: May 5 - June 11, Tuesdays and Thursdays, 5-8pm in MY370 Add Deadline: May 11 Drop Deadline: June 1 | x | |||
| APS1022H: Financial Engineering II | To drop this course, please use course add/drop form, with your signature and submit to d.duong@utoronto.ca | SUMMER 2026: May 4 - May 15, Daily Monday to Friday, 10am-1pm, in SF2202 Exam on Saturday May 16 Course add deadline: May 5 Course drop deadline: May 8 | x | ||
| APS1028H: Operations and Production Management for Manufacturing and Services | WINTER 2026: 100% Online, Kick off - Jan 5 - April 14, Monday, Jan 6, 1-4PM | x | |||
| APS1032: Introduction to Energy Project Management | FALL 2025: Sept 8 - Dec 22, Mondays 5-8pm in MS3278 | x | |||
| APS1049H: Management Consulting For Engineers | FALL 2025: Sept 8 - Dec 8, Monday, 1-4pm, in-person kick off class Sept 8 in AB114 SUMMER 2026: May 19 - June 5, Daily class, Monday-Friday, Starts May 19, 1pm-4pm. Week 2, no class except May 26, Week 3 resume class on June 1. Room in MY440 Course add deadline: May 19 Course drop deadline: May 21 | x | x | ||
| APS1050H: Blockchain Technologies And Cryptocurrencies | FALL 2025: Sept 12 - Dec 12, Fridays, 5-8pm in BA1190 WINTER 2026: Jan 16 - April 10, Fridays, 5-8pm in BA1170 SUMMER 2026: May 22 - Aug 14, Fridays 5-8pm, BA1190 Course add deadline: May 23 Course drop deadline: June 22 | x | x | x | |
| APS1051H: Portfolio Management Praxis Under Real Market Constraint | FALL 2025: Sept 10- Dec 10, Wednesdays, 5-8pm in BA1200 WINTER 2026: Jan 14 - April 8, Wednesdays, 5-8pm in ESB142 SUMMER 2026: May 13 - Aug 12, Wednesdays, 5-8pm, BA1180 Course add deadline: May 14 Course drop deadline: June 22 | x | x | x | |
| APS1052H: A.I. in Finance | FALL 2025: Sept 11 - Dec 11, Thursdays, 5-8pm in MC254 WINTER 2026: Jan 15 - April 9, Thursdays, 5-8pm in SS2117 (correction from MS2172) SUMMER 2026: May 14 - July 6, Thursdays 5-8pm, BA1130 Course add deadline: May 15 Course drop deadline: June 22 | x | x | x | |
| APS1053H: Case Studies in AI in Finance | FALL 2025: Sept 9 - Dec 16, Tuesdays, 5-8pm in BA B024 WINTER 2026: Jan 13 - April 7, Tuesdays, 5-8pm in BA2195 | x | x | ||
APS500H1: Negotiations in an Engineering Context
Instruction of concepts, theories, and research but most importantly the practice of negotiation skills. The course will cover all kinds of negotiations scenarios that individuals might face in the course of their careers as Engineers; this could include a range of single-issue single-party negotiations to multi-party multi-issues negotiations.
APS502H1: Financial Engineering
Roy Kwon
This course will focus on capital budgeting, financial optimization, and project evaluation models and their solution techniques. In particular, linear, non-linear, and integer programming models and their solutions techniques will be studied. The course will give engineering students a background in modern capital budgeting and financial techniques that are relevant in practical engineering and commercial settings.
APS1001H: Project Management
Darya Duma | Course Syllabus
Course intro here. Project management has evolved from being an accidental job title into being a chosen profession with career paths and a body of knowledge. This course covers most of the knowledge areas of the Project Management Institute: integration, scope, cost, time, risk, human resources, procurement and communications management. We take a practical, applied approach, with the “PMBOK Guide” textbook, in-class exercises, and a team paper on “lessons learned” from an actual project. This a completely asynchronous online course.
This course is open only to MEng students.
APS1004H: Human Resources Management: An Engineering Perspective
Tom Stephenson
This course analyzes the relationship between management and workers in an engineering (including construction and manufacturing) environment. The course takes a holistic and strategic view of how industrial relations affect the business environment. Students will study industrial relations from the context of engineering-related industries, economics, sociology, and psychology. Students will develop an historical appreciation and perspective of the evolution and development of labour relations through concepts presented by figures such as Adam Smith, Fredrick Taylor, Charles Deming, and J.M. Juran. The goal of the course is to provide a general manager with a thorough understanding of how they can develop a competitive advantage for their organization through effective and thoughtful human resource management practices. In the context of how they relate to engineering and industrial relations, the course topics include: organizational behaviour including methods of motivation, scientific management, quality control, employment and economics, employment as a social relation, unions and other forms of employee representation, internal labour markets, strategic planning and the formulation of human resource strategy, practices and policies.
APS1005H: Operations Research for Engineering Management
Roy Kwon
This course introduces optimization techniques applicable in solving various engineering programs. These techniques are widely used in engineering design, optimal control, production planning, reliability engineering, and operations management. The contents of this course can be classified into two major categories: modeling techniques and optimization algorithms. Topics include linear programming, sensitivity analysis, nonlinear programming, dynamic programming, decision making under uncertainty, new developments in optimization techniques. The course will also examine several case studies to gain understanding of real applications of optimization techniques.
APS1009: Natural Resources Management
Eduardo Fernandez
This course focuses on management of projects on Natural resources and offer graduate engineering students the opportunity to learn specific management skills and management tools, from a holistic view of issues related to the management of natural resource projects and enterprises, and the required knowledge to identify and develop sustainable solutions to the interdisciplinary challenges related to the sustainable management of natural resources projects. The course also considers the management of public enterprises that are in charge of planning and developing national resources and important sustainable national and regional natural resources projects, such as water, environment, energy, minerals resources, or biological resources, not only in Canada, but also internationally. This course will help students to develop the necessary skills and capabilities needed and required in real life from graduate engineers, to be able to work successfully in natural resources management and natural resources projects and enterprises, whether working with the public sector or private sector, or in P3-Public Private Partnership and projects or working with a non-governmental organization, These skills will enable the students to work with different stakeholders,thinking strategically and keeping in mind always, the social responsibility as a core of all the projects related to natural resources. The course utilizes lectures, guest speakers,class discussions and analysis on real cases, and requires students to write and present a final team project report.
APS1016H: Financial Management for Engineers
Babu Gajaria
The students will be exposed to classical equity valuation methods; such as discounted cash flow analysis, net asset value, fundamental analysis and relative value analysis, using measures such as P/E multiples and P/Cash flow multiples. The students will be introduced to the principles of bond and stock valuations with a special emphasis on its relation to the cost of capital. The course will take an in depth view of capital budgeting, capital investment decisions and project analysis and evaluations. It will introduce students to the concept risk and return in equity markets. The students will get hands on experience in calculating cost of capital and hence the appropriate discount rate to use in valuations. Theory of optimal capital structure and financial leverage will be discussed in addition to economic value added principles. The relevance of dividends and dividend policy will be debated in class. The concept of “does dividend policy matter” will be subject of a vigorous debate. Finally the topic of mergers and acquisitions will be covered in depth, with particular reference to recent mergers of Canadian companies.
APS1017H: Supply Chain Management and Logistics
C.G. Lee
This course is to provide students with a framework to design and control supply chain systems. To achieve the goal, the course will cover key modules in supply chain. The students will be exposed to topics such as: inventory theories, transportation, postponement strategies, supply chain dynamics, value of information, supply chain flexibility, and environmental issues. We will focus on the analytical decision support tools (both models and applications), as well as on the organizational models that successfully allow companies to develop, implement and sustain supplier management and collaborative strategies.
APS1020H: International Business for Engineers
APS1020H Syllabus | Weekly Schedule
Eduardo Fernandez
This course-Summer 2026- provides a background on international business for all engineering and applied science disciplines through "hands-on" project work and BUSINESS CASES. Each week there will be class discussion on a business case and/or on new business concepts and learning a new Business Management tool as part of the weekly learning and assignments. This course goes beyond merely learning the basic concepts of international business 2026 We will use real life examples to practice and debate the different principles historically used to pursue a modern cross-border operation but updated at present- 2026. The intention is not to bury the student with information, but rather by providing context to enable deeper learning and so provide what will be for many their first true international business course. It is about not just the knowledge, but the practical skills and management tools needed when pursuing business across borders. You will get an understanding of the current issues (2026), such as trade tariffs and trade conflicts, inflation, possible recession, current interest rate environment and Supply chain restrictions/disruptions and current trade stress between USA vs China, Canada, EU, and UK’s post-Brexit; Also, the current geopolitical events in Canada ,The Americas, the whole continent, and how those events may affect Canada in late 2026 and possibly in 2027. Europe, Asia and Africa current business trends, opportunities, and Risks in emerging markets and in the Global South. Also, how Houthi attacks on ships in Red Sea, wars in Ukraine and in the Middle East, affect supply chains and energy transition 2026.
Corporate Social Responsibility is a core part of this course. We will have different internationals experts as guest speakers on international issues during this course APS1020- Summer 2026.
APS1022H: Financial Engineering II
Roy H. Kwon, C.G. Lee
The course presents two important topics in financial engineering: portfolio optimization and derivative pricing. These two topics are explored by the application of a number of mathematical tools, including linear programming, nonlinear programming, statistical analysis, and the theory of stochastic calculus.
APS1028H: Operations and Production Management for Manufacturing and Services
APS1028 Syllabus | APS1028 Summer Syllabus
Operations Management is the systematic approach and control of the processes that transform inputs (e.g. human resources, facilities, materials, processes, enterprise management information systems, etc.) into finished goods and services. The operations function consists of the core wealth creation processes of a business and helps an organization to efficiently achieve its mission while constantly increasing productivity and quality. This course focuses on the role of operations management as a strategic element of the total organization. We will cover classic and up-to-date tools and concepts used to support operational managerial decisions in variety of industry sectors both in manufacturing and the service sector. The course covers areas such as strategy, product design, process design, plant location and plant layout, inventory management, role of technology in OM, HRM, Socio-Tech Systems, Group Technology, ERP / CIM, Quality Management, Maintenance Management. The course is tailored for engineers that aspire to senior management positions starting as departmental / functional managers of operations or engineering, and then progressing to directors, VP Operations, VP Manufacturing and eventually becoming a Chief Operations Officer (COO) or C-Level Certified Management Consultants in small to large scale enterprises. This course will incorporate academic scholarly readings to provide the broad theory of OM but most of the readings and discussions will be based on the instructors many years of hands on practical experience in OM in a variety of industry sectors.
APS1032: Introduction to Energy Project Management
Payam Rahimi
Project management is important for any business organization, but particularly so for the energy industry. Sufficient controls are needed during initiation, study, implementation, and closeout of any energy project, and project managers within the energy environment (such as oil, gas, nuclear, …) face unique challenges and important risk management considerations. This course will expose students to best project management practices within the context of the energy industry. The course will introduce the particular characteristics of managing energy projects from the planning phase to closeout. Environmental assessments, geopolitical considerations, the political landscape, risk management and the roles of different players will be discussed. Tools to monitor the health and progress of a project will be introduced. Examples of different types of energy projects in the fields of nuclear, bio-mass, oil, gas, wind and solar will be used to illustrate concepts.
APS1049H: Management Consulting For Engineers
APS1049H Syllabus | APS1049H Summer Syllabus
Management Consulting will continue to be a significant career option for many graduate students, regardless of whether a student’s academic foundation is in business, engineering, or the basic sciences. Careers in Management Consulting often provide individuals an opportunity for challenging work, continued self-development, access to important social and professional networks, and, over time, significant financial rewards. This course is designed to enable graduate engineers explore, and prepare for a career in management consulting. The course is taught by Fellow Certified Management Consultant (FCMC), licensed professional engineer, and as an entrepreneur built and sustained a management consulting business over a period of 25 years. The Global Management Consulting Industry has grown in size and complexity particularly since the early 1990’s. Although there are many small niche firms, the industry is dominated by a relatively few very large global organizations that practice in a variety of business settings and business disciplines. In addition many businesses have developed internal consulting organizations to provide consulting related services within the organization and often in conjunction with external consulting services offered by third party firms. In this course we explore what it means to be a Management Consultant, and will introduce students to consulting frameworks and methods; simulate consulting project activities and situations using business cases; and network students with practicing consulting professionals from a variety of global and local firms. Within the context of this course, consulting is viewed broadly and is inclusive of a number of practice areas including Strategy , IT and Systems Integration, Marketing, Human Resource Management, Operational / Process / Supply Chain, Organizational Development, and the very specialized area of Engineering and Product Development Management. Consulting also cuts across a wide variety of industry sectors from public sector (government, health care, infrastructure, defense etc), to private sector (manufacturing, oil gas, natural resources), Course participants will be organized into teams and will have the opportunity to identify and complete a project on the practice of management consulting that is aligned to the emerging needs of the profession (collaborating with external partner firms). In addition students will wear an entrepreneurial hat, and will be required to develop an individual blue print, and business plan of their future management consulting business which might be in an emerging field of consulting such as life sciences, data analytics, cyber security, crowdsourcing and digital strategy.
APS1050H: Blockchain Technologies And Cryptocurrencies
Loren Trigo and Sabatino Costanzo
Bitcoin is a particular implementation of Blockchain technology that has led to a disruptive “product”: a set of digital cryptocurrencies with the potential to compete with fiat currencies. This course will provide students with the concepts and mechanics of the Blockchain technologies starting from Bitcoin. Unlike ECE1770, this course is not focused on middleware software design per se, but on how the Blockchain middleware can serve as a platform that supports products (cryptocurrencies, tokens) and applications that are relevant for businesses and other users. Students become acquainted with the history and typology of Blockchain technologies; develop and apply a set of selection criteria for the evaluation of Blockchain consensus strengths, weaknesses and risks; trace a likely path for the adoption of Blockchain technologies-- beginning with the identification of processes where Blockchain ledgers lead to efficiencies, to the emergence of new business models where the use of cryptography is essential. For this reason, this course includes a gentle but complete introduction to cryptography that covers all the essentials from asymmetric encryption to “zero-knowledge-proof-of-knowledge” proofs. On a practical level, participants acquire a concrete understanding of Blockchain technologies through the installation, operation and modification of a number of Blockchain technologies that operate in real-world testnet networks: starting from the operation/modification of a simple Bitcoin node; moving on to the operation of Bitcoin and Ethereum wallets, and to the operation/modification of Ethereum clients or DApps providing a business service, and ending with the trading of a cryptocurrency account. For more details please go to the Course Layout section of the Syllabus.
APS1051H: Portfolio Management Praxis Under Real Market Constraint
Sabatino Costanzo and Loren Trigo
After an introductory review of the techniques most commonly used to evaluate investment portfolios and investment managers and an overview of the theoretical foundations of modern finance, this course will, through a combination of lectures, readings, real case studies and hands-on exercises, enable students to learn how to use --in real time and under real constraints--, the five main algorithmic trading & portfolio management systems developed by the instructors to manage their own clients’ investment portfolios in their professional private practice. After completing this course the participants should be able to manage basic Stocks and ETF portfolios as well as trading currency pairs and basic derivatives portfolios of Credit & Debit Spreads, by using time-tested “value” and “momentum” strategies, statistical-arbitrage pairs-trading techniques and covered options algorithms, all coded in the python programs developed by the instructors to that end. Students will also be able to manage the risk of any basic investment portfolio using index-option’s hedging and/or market breadth- based algorithms, and to apply the best known tests to evaluate the back-testing results of different trading systems. As collateral benefits of this course, participants will be exposed to the basics of python in finance -as they learn how to calibrate the trading software shared by the instructors-, as well as to basic equity valuation methods, basic portfolio optimization methods and basic bond and derivative pricing methods. Participants will be also exposed through case studies to the portfolio management strategies of some of the most important contemporary portfolio managers and apply digested versions of their techniques to basic portfolios under real market constraints. In the long run, after having assimilated and tested what they’ve learned in this course, students should be able to assemble general portfolio management strategies well adapted to their own risk/return profiles. For more details please go to the Course Layout section of the Syllabus.
APS1052H: A.I. in Finance
Sabatino Costanzo and Loren Trigo
Course Description:
In this course we’ll give an overview of several applications of machine learning to capital market forecasting and credit modeling, beginning with regressions, “shallow” layered machine learning models (e.g. Support Vector Machines, Random Forests), and ending with “deep” layered machine learning models (e.g. Long Short Term Memory Networks). Each model is discussed in detail as to what input variables and what architecture is used (rationale), how the model’s learning progress is evaluated and how machine learning scientists and capital market traders evaluate the model’s final performance so that by the end of the course, the students should be able to identify the main features of a machine learning model for capital market forecasting and to evaluate if it is likely to be useful and if it is structured efficiently in terms of inputs and outputs.
The course covers (but it is not limited to) the following subjects: Training and testing workflow: scaling, cross-validation pipelines. Gradient descent: mini-batch, stochastic. Financial metrics: profitability and risk. Financial feature engineering. Models: multivariate regression, logistic regression, support vector machines, principal component analysis, decision trees, random forests, k-means, and hierarchical clustering, Gaussian mixtures, MLPs, LSTMs, and auto-encoder neural networks. Applications: credit modeling, financial time-series forecasting, investment portfolio design, and spread trading, credit cycle regime identification. For more details, please see the Course Layout in the Syllabus.
In terms of requisites, the participant should be familiar with the foundations of statistics, the basics of logistic regressions (desirable), and basic linear algebra (desirable); however, since our course intends to be self-contained, we will provide a review of these concepts as needed. As the examples of our course come from finance, some familiarity with capital markets and the basic financial concepts is recommended. Basic knowledge of Python or some other programming language is recommended, even though the objective of the course is not to learn how to program (shallow & deep) machine learning models from scratch, but rather, to understand how they work and to learn how to adapt them to the particular needs of the user and to optimize their application to market forecasting. The mathematical foundations of the basic machine learning models (regressions, neural networks, support vector machines, trees etc.) will be discussed and followed by a panoramic view of the inputs that are most likely to provide valuable information for market forecasting. Standard benchmarking methods used in the industry will be also covered. Subsequently, a number of basic --already programmed-- models will be discussed in detail and their performance evaluated.
APS1053H: Case Studies in A.I. in Finance
Sabatino Costanzo and Loren Trigo | Syllabus
Course Description:
This course is built around a large collection of real-world case studies, providing hands-on applications of many topics covered in the courses we've taught. Designed as a seminar, it offers a unique, informal, collegiate learning atmosphere. Participants are treated as colleagues rather than students, fostering both collaboration and accountability. The seminar begins with a series of introductory sessions, delivered by the instructors (and potentially guest speakers), to establish the theoretical foundations necessary for understanding the topics in depth. These sessions, scheduled before a week break, will range from “A Basic Finance Primer” to “A Comprehensive Introduction to Reinforcement Learning applied to Finance.”After the week break, the course transitions into student-led sessions where participants present assigned case studies. These presentations are an opportunity to apply theoretical knowledge to practical problems and to engage in meaningful discussions with peers. As part of our long-term vision for this seminar—to establish a stable platform for promoting FinTech research—we are welcoming back all past students who registered in previous editions of this course and who would like to attend to help transform this seminar into a wider, thriving, professional community dedicated to FinTech. More specifically, this course explores the application of advanced artificial intelligence techniques through a large collection of solved case studies in areas such as stock trading and hedging strategies, portfolio construction, options modeling, investor profiling, financial news generation, robotic advisors, and more. Topics include the use of cutting-edge open-source libraries for calculating and evaluating financial indicators, developing custom functions for cross-validation and model selection, reformulating problems using reinforcement learning, implementing Python-based reinforcement learning solutions, and analyzing scenarios where such techniques fall short.
Course Structure: (i) Instructor-Led Sessions: the initial sessions will cover theoretical foundations and will be delivered by the instructors. (ii) Student-Led Sessions: subsequent sessions will feature student presentations of assigned case studies. These presentations will delve into the theoretical frameworks, financial principles, AI techniques, coding implementations, and opportunities for improvement or extension. Students will work from a collection of solved case studies provided by the instructors and will be evaluated based on their assigned case study-related work.
Prerequisites: no specific prerequisites are required, apart from very basic programming skills, some familiarity with financial terms and a strong interest in the practical applications of AI in solving real-world financial problems.
MIE Technical Course Classification: in credit terms, this course (APS1053) is classified as a "Technical" course; it has the same credit classification and credit value as APS1050, APS1051 and APS1052.
Source Books: Reinforcement Learning for Finance by Hilpisch; Machine Learning Blueprints for Finance by Tatsat; Machine Learning for Financial Risk Management with Python by Karasan; Hands-on Unsupervised Learning Using Python by Patel; Deep Learning for Finance by Kaabar; Machine Learning for Finance by Klaas.