Choose from these special topics courses to complement your University of Toronto Mississauga Management (UTMM) program. Learn current trends and practices in business from Management faculty. Check your program details because many allow these courses to count towards program completion.
MGT 311H5 MACHINE LEARNING
Term: Winter - Professor G. Trippen
This course introduces a diverse collection of big data techniques, often aimed at identifying and quantifying various structures in data. Learn model validation and the effective communication of model-based results. The course employs a “white-box” methodology, which emphasizes an understanding of algorithmic and statistical model structures, and use Python to apply different algorithms to real-world big data. Recommended prerequisite: MGT270H5 or MGT201H5
MGT312H5 PROJECT MANAGEMENT (NEW)
Term: Winter - Professor O. Bountali
This course will prepare you for a successful career in environments that organize work using projects. Projects play a critical role in achieving the strategic goals of an organization and organizations often pursue projects for innovation, change, and gaining competitive advantage. Hence, the use of project management tools, techniques and methodologies is becoming ubiquitous. The project management course, therefore, focuses on principles, tools, and techniques required for managing projects successfully. Using the framework of a project life cycle, the course introduces students to the proper terminology and familiarizes them with the theory behind. We will cover various aspects pertaining to (i) project selection, (ii) planning and scheduling, (iii) monitoring and control and (iv) risk management. Scheduling of projects with resource limitations, role of incentives in project management, and project contracting will be also included. Moreover, an overview of Agile Project Management, Organization Structure, and Project Management approaches will be covered. Ultimately, the course will help you function successfully when being part of a designated project team and help prepare you for CAPM certification.
Term: Fall - Professor A. Park
This course is an introduction to the economics of blockchain technology and its applications to finance. Discuss the functioning of blockchains; fundamentals of cryptography; zero-knowledge proofs; the economics of decentralized platforms; stablecoins and blockchain monetary policy; tokenomics, tokenization, and the usage of tokens in finance; decentralized banking applications; decentralized exchanges and crypto trading. Recommended prerequisite: ECO204Y5 and MGT120H5
MGT412H5 BUSINESS STRATEGY FOR THE DIGITAL ECONOMY (NEW)
Term: Fall - Professor E. H. Caoui
This course introduces core strategy concepts applied to technology companies, e-commerce, and digital markets. It will identify the critical features that differentiate technology firms such as Google, Facebook/Instagram, Amazon, and Uber, from traditional industries, and examine the implications for business strategy. It will cover topics such as network effects, switching costs, and platform markets. To complement the theory, we will also consider case studies of technology firms, with an aim to provide real-world applications to concepts developed in class and enhance your written, rhetorical and presentation skills. Recommended prerequisite: ECO204Y5 and MGT120H5
MGT414H5 DIGITAL MARKETING (NEW)
Term: Winter - Professor H. Yoo
More information coming soon!
Recommended prerequisite: MGT252H5
MGT415H5 Valuation: Fundamentals and Data (NEW)
Term: Winter - Professor A. Chattopadhyay
More information coming soon!
Recommended prerequisite: TBD
MGT 416H5 ENTERPRISE RISK MANAGEMENT
Term: Fall - Professor O. Yung
This course studies risk management from a holistic perspective for various institutions (i.e. non-financial and financial). Various risk categories will be considered such as cyber risk, operational risk, market risk, energy risk, technology risk, financial risk, etc. Leading edge cases and frameworks will be integrated into the course. Recommended prerequisite: MGT231H5 and MGT270H5 (or co-requisite)
MGT417H5 PREDICTIVE ANALYTICS
Term: Winter - Professor A. Steck
Learn a variety of models and techniques used in predictive analytics. These include linear and nonlinear regression, classification algorithms, causal inference, and machine learning techniques such as random trees and reinforcement learning. The class emphasizes: 1) developing a conceptual understanding and interpretation of the models and 2) using hands-on applications to build experience and reinforce concepts. The programming exercises use the popular R programming language. Recommended prerequisite: ECO220Y5 or STA256H5, and STA258H5 or STA260H5, and ECO375H5