Program Requirements
The Major in Business Analytics offers an interdisciplinary approach to study the evolving field of management analytics with a strong emphasis on experiential learning. The major is designed to address the growing needs of organizations for business analytics, data science, and artificial intelligence. The emphasis of the program will be on managerial issues and use of state-of-the-art data analytics tools to optimize organizational decisions in a variety of managerial settings.
Required Courses (51 credits)
Management Core
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MGCR 211 Introduction to Financial Accounting (3 credits)
Overview
Management Core : The role of financial accounting in the reporting of the financial performance of a business. The principles, components and uses of financial accounting and reporting from a user's perspective, including the recording of accounting transactions and events, the examination of the elements of financial statements, the preparation of financial statements and the analysis of financial results.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Restriction: Not open to U0 students.
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MGCR 222 Introduction to Organizational Behaviour (3 credits)
Overview
Management Core : Individual motivation and communication style; group dynamics as related to problem solving and decision making, leadership style, work structuring and the larger environment. Interdependence of individual, group and organization task and structure.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Restriction: Not open to U0 students.
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MGCR 250 Expressive Analysis for Management.
(3 credits)
Overview
Management Core : Focusing on skills with respect to analysis, writing and presentation in management.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Open to U0 and U1 B.Com. students. Not open to students who have taken BUSA 250.
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MGCR 271 Business Statistics (3 credits)
Overview
Management Core : Statistical concepts and methodology, their application to managerial decision-making, real-life data, problem-solving and spreadsheet modeling. Topics include: descriptive statistics; normal distributions, sampling distributions and estimation, hypothesis testing for one and two populations, goodness of fit, analysis of variance, simple and multiple regression.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Restriction: Not open to U0 students. Not open to students who have taken or are taking ECON 227D1/D2, ECON 257D1/D2, MATH 203 at McGill, MATH 204, MATH 324, PSYC 204; students with an exemption from High School or CEGEP for MATH 203 will NOT be exempt from MCGR 271.
You may not be able to receive credit for this course and other statistic courses. Be sure to check the Course Overlap section under Faculty Degree Requirements in the Arts or Science section of the Calendar.
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MGCR 293 Managerial Economics (3 credits)
Overview
Management Core : The course focuses on the application of economic theory to management problems and the economic foundations of marketing, finance, and production. Attention is given to the following topics: price and cost analysis; demand and supply analysis, conditions of competition.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Restriction: Not open to U0 students. Not open to students who have taken or are taking ECON 208, ECON 230D1/D2, or ECON 250D1/D2.
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MGCR 294 The Firm in the
Macroeconomy (3 credits)
Overview
Management Core : Topics and tools of macroeconomics such as national accounting, the IS-LM model, the drivers of output and business cycles, and the basics of monetary policy and inflation. Emphasis on financial markets, the role of expectations, and the reasons for possible deviations from full information market efficiency.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Corequisites: MGCR 293
Restrictions: Open only to B.Com. students. Not open to students who have taken or are taking ECON 295, ECON 209, ECON 330D1/D2 or ECON 352D1/D2.
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MGCR 331 Information Technology Management
(3 credits)
Overview
Management Core : Introduction to principles and concepts of information systems in organizations. Topics include information technology, transaction processing systems, decision support systems, database and systems development. Students are required to have background preparation on basic micro computer skills including spreadsheet and word-processing.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Restriction: Not open to U0 students.
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MGCR 341 Introduction to Finance (3 credits)
Overview
Management Core : An introduction to the principles, issues, and institutions of Finance. Topics include valuation, risk, capital investment, financial structure, cost of capital, working capital management, financial markets, and securities.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Corequisite: MGCR 271 or equivalent
Restriction: Not open to U0 students.
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MGCR 352 Principles of Marketing (3 credits)
Overview
Management Core : Introduction to marketing principles, focusing on problem solving and decision making. Topics include: the marketing concept; marketing strategies; buyer behaviour; Canadian demographics; internal and external constraints; product; promotion; distribution; price. Lectures, text material and case studies.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Restrictions: Open to U1, U2, U3 students.
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MGCR 372 Operations
Management.
(3 credits)
Overview
Management Core : Design, planning, establishment, control, and improvement of the activities/processes that create a firm's final products and/or services. The interaction of operations with other business areas will also be discussed. Topics include forecasting, product and process design, waiting lines, capacity planning, inventory management and total quality management.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
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MGCR 382 International Business (3 credits)
Overview
Management Core : An introduction to the world of international business. Economic foundations of international trade and investment. The international trade, finance, and regulatory frameworks. Relations between international companies and nation-states, including costs and benefits of foreign investment and alternative controls and responses. Effects of local environmental characteristics on the operations of multi-national enterprises.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Restriction: Not open to U0 students.
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MGCR 423 Strategic Management (3 credits)
Overview
Management Core : An integrative and interdisciplinary introduction to strategy formation and execution. Concepts, tools, and practical application to understand how firms leverage resources and capabilities to gain competitive advantage in dynamic, contemporary industries. Strategic positioning, organizational design, and managerial action for the long-term success of businesses and positive social and ecological outcomes.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Restriction: Open to U2, U3 students only
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MGCR 460 Social Context of Business.
(3 credits)
Overview
Management Core : Examination of how business interacts with the larger society. Exploration of the development of modern capitalist society, and the dilemmas that organizations face in acting in a socially responsible manner. Examination of these issues with reference to sustainable development, business ethics, globalization and developing countries, and political activity.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Restrictions: Open to U2 and U3 students. Not open to students who have taken MGCR 360.
Major
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INSY 336 Data Handling and Coding for Analytics (3 credits)
Overview
Information Systems : Preparation and analysis of data for business analytics. Topics include: data acquisition, data manipulation and computer programming for statistical analysis.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Prerequisite: MGCR 331
Restrictions: Open to U2 and U3 students.
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INSY 446 Data Mining for Business Analytics (3 credits)
Overview
Information Systems : Practical methods and techniques for data mining and predictive analytics to solve business problems. Use of statistical tools for hands-on learning. Topics covered include supervised learning, unsupervised learning, and text mining.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Corequisite: INSY 336
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MGSC 404 Foundations of Decision Analytics (3 credits)
Overview
Management Science : This course teaches quantitative methods used in business decision making. Topics include: optimization models, decision trees, simulation, and computer simulation. Business applications of these techniques are emphasized. Students in this course will acquire expertise in computer based methods for decision making, through computer analysis of real-life problems.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Restrictions: Open to U2 and U3 students.
3 credits of experiential learning from the following:
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MGSC 483 Analytics-Based Community Project (3 credits)
Overview
Management Science : Aiding a host community organization in the application of analytics, with the aim of helping to improve the community's operations for the good of society.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Prerequisite: Permission of Instructor
Restrictions: Only open to U3 students.
This interdisciplinary experiential-learning course will partner students with an NGO to draw on that organization’s knowledge in sustainability or analytics. During these projects, students will implement AI and analytical tools to, for example, study the health of bee colonies, track microplastics in the ocean, help micro-farming initiatives, or develop compost optimization. Students will earn credits from McGill University by developing experiential, all while living on a natural reserve in Costa Rica located steps away from Playa Conchal.
There is an additional fee of $3050 that covers accommodation for 10 nights in Costa Rica, all ground transportation, entrance to national parks and natural reserves, most meals, and all course infrastructure and materials.
**Due to the intensive nature of this course, the standard add/drop and withdrawal deadlines do not apply. Course Add is the fourth lecture day.
**Web ADD only.
**No web drop allowed.
**Web withdrawal not applicable.
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RETL 407 Retail Management Project (3 credits)
Overview
RETL : A team-based, experiential project that involves defining actual problems and recommending solutions in the realm of an organization, or at the interface of different organizations (e.g. supply chains), including strategic and operational issues in retail management. Each project is multidisciplinary or multi-functional in nature and will have significant impact on one or more operational/competitive capabilities of the organization.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Restricted to U2 & U3 students.
The instructors will make sure that the workload of the project is commensurate with the course credit and team size.
The instructors will also be involved during the course as advisers, progress reviewers, logistics coordinators, evaluators, and will serve as liaison between the companies and the teams
Complementary Courses (18 credits)
3-6 credits from the following:
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MGSC 401 Statistical Foundations of Data Analytics (3 credits)
Overview
Management Science : This course will provide statistical foundations for data analytics. In this course, we will learn an introduction to advanced statistical techniques and methodologies including sampling, regression, time-series and multi-variate statistics. We will support our approach by looking at applied examples and real cases and datasets across several business areas, including marketing, human resources, finance, and operations. Students will apply their skills to interpret a real-world data set and make appropriate business recommendations.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Prerequisite(s): MGCR 271 or equivalent.
Restrictions: Open to U2 and U3 students
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MGSC 416 Data-Driven Models for Operations Analytics (3 credits)
Overview
Management Science : Examination of how data-driven models have been used to transform businesses and industries, using examples and case studies in e-commerce, retail, social and online networks, sports analytics, and online advertising. Demonstration of the use of data-driven analytics methods such as time series forecasting, network models, mixed-integer optimization, matching markets and exploration/exploitation.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
6-9 credits of technical component from the following:
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INSY 437 Managing Data and Databases (3 credits)
Overview
Information Systems : Management of organizational data, implementation of database management systems, and the roles and responsibilities of data management personnel. Explores different models of data representation with an emphasis on the relational model; simple and complex SQL queries.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Prerequisite: MGCR 331
Management: students are encouraged to take this course as early as possible in their program.
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INSY 442 Data Analysis and Visualization (3 credits)
Overview
Information Systems : Overview of methods and tools for analyzing business data to improve business decision-making, focusing on data visualization using hands-on learning.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Prerequisites: MGCR 331 or permission of the instructor and approval of the BCom ProgramOffice.
Restriction(s): Open to U2 and U3 students.
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INSY 463 Deep Learning for Business Analytics (3 credits)
Overview
Information Systems : Theory of Neural Networks and its applications for business analytics, including how to build and train Neural Networks to derive insights from unstructured text and image data in business contexts. Introduction to the ecosystem of software packages needed in Python, including: NumPy, Pandas, Sklearn. The theory and implementation of Neural Networks and Deep Learning. How to apply various deep learning models to real-world problems and demonstration of their power in the new data-abundant business world.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
3-9 credits from the following:
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ACCT 451 Data Analytics in Capital Market (3 credits)
Overview
Accounting : Exploration of how financial and non-financial metrics can be linked to business performance through experiential learning, with a focus on financial statement analysis, earnings and return predictability, textural analysis, earnings management and fraud detection. Introduction to SAS software and financial accounting databases such as CRSP, Compustat, and I/B/E/S, and alternative data sources such as SEC Edgar that enables work across different database to make better financial statement analysis and decisions.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
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BUSA 471 Artificial Intelligence Ethics for Business (3 credits)
Overview
Business Admin : Frameworks to highlight model explainability, data anonymity and privacy, bias and fairness. Analytical tools that will allow managers to incorporate these ethical concerns during artificial intelligence development and deployment.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Prerequisite: INSY 336
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FINE 460 Financial Analytics (3 credits)
Overview
Finance : An extensive study of the empirical methods casually used in the different subfields of finance. Examination of the most popular statistics models used in finance, both from a theoretical and practical point of view. An important emphasis will be put on the distinction between models of financial mechanisms, and those motivated purely by efficacy.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Prerequisites: MGCR 341
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INSY 448 Text and Social Media Analytics (3 credits)
Overview
Information Systems : The unlimited opportunities that exist today to leverage the power of user generated content analytics, focusing on questions ranging from strategic to operational matters pertaining to a firm’s social media initiatives, metrics to capture relevant outcomes, and predictive analysis to link social media chatter to business performance.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
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MRKT 440 Marketing Analytics (3 credits)
Overview
Marketing : Analytic techniques available to marketing managers including practice with actual data sets to use the techniques. Topics covered will include customer and product analytic models, digital marketing, and marketing resource allocation.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
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MRKT 442 Customer Analytics (3 credits)
Overview
Marketing : Identification of common data science solutions to customer analytics. What, when, where and how to collect customer data. Basic customer analysis and assessment of the influence of marketing programs on business performance and customer satisfaction. Insights gained from analytics to a non-technical audience. Examination of the cutting edge applications of customer analytics and emerging trends.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Prerequisite: MGSC 401
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ORGB 330 People Analytics (3 credits)
Overview
Organizational Behaviour : This is the era of big data. Companies and organizations are collecting an enormous amount of information and we are only just beginning to grasp the ways in which this information might be used. This course covers the emerging field of people analytics, which involves applying data collection and analysis techniques to improve the management of people within organizations. We will cover current people analytics techniques, common pitfalls, and possible shortcomings of people analytics, as well as the ethical questions involved in undertaking such analyses.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Or any related undergraduate topics course (with approvals from the Business Analytics area and the B.Com. Office).
