Program Requirements
The core module is designed to teach the fundamentals of data and decision analytics, team management, and leadership. The complementary course module is designed to expose students to a variety of management analytics application topics including marketing, retailing, supply chain, healthcare, security, pricing, talent and network analytics. Finally, the experiential module, which consists of a capstone management analytics project plus a community project or internship, is designed to provide students with the experience of hands-on application of the concepts taught in real-world settings and the opportunity to interact with practitioners in leading analytics organizations.
Required Courses (27 credits)
Note: Students take either BUSA 693 D1 and BUSA 693 D2 or BUSA 693 N1 and BUSA 693 N2.
-
BUSA 693D1 Analytics and Solution Consulting Practicum (3 credits)
Overview
Business Admin : Data science teams working with a dedicated client to solve data/analytics challenges, including building an analytically-accurate and technically-automated solution.
Terms: Fall 2024
Instructors: Hosain, Shoeb (Fall)
Students must also register for BUSA 693D2
No credit will be given for this course unless both BUSA 693D1 and BUSA 693D2 are successfully completed
-
BUSA 693D2 Analytics and Solution Consulting Practicum (3 credits)
Overview
Business Admin : For description see BUSA 693D1.
Terms: Winter 2025
Instructors: Hosain, Shoeb (Winter)
Prerequisite: BUSA 693D1
No credit will be given for this course unless both BUSA 693D1 and BUSA 693D2 are successfully completed
-
BUSA 693N1 Analytics and Solution Consulting Practicum (3 credits)
Overview
Business Admin : Data science teams working with a dedicated client to solve data/analytics challenges, including building an analytically-accurate and technically-automated solution.
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.
Students must also register for BUSA 693N2
No credit will be given for this course unless both BUSA 693N1 and BUSA 693N2 are successfully completed in a twelve month period.
Prerequisite(s): INSY 660, INSY 661, INSY 662, MGSC 660, MGSC 661, MGSC 662, ORGB 660, ORGB 661.
**This course will be held on August 5, 7, 9, 12, 14, 16, 21, 22 & 30.
**Due to the intensive nature of this course, the standard add/drop and withdrawal deadlines do not apply. Course Add is the second lecture day.
**No web drop allowed.
**Web withdrawal not applicable.
-
BUSA 693N2 Analytics and Solution Consulting Practicum (3 credits)
Overview
Business Admin : See BUSA 693N1 for description.
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: BUSA 693N1
No credit will be given for this course unless both BUSA 693N1 and BUSA 693N2 are successfully completed in a twelve month period
-
INSY 660 Coding Foundations for Analytics (3 credits)
Overview
Information Systems : Students will be exposed to a broad set of topics, including fundamentals of computer programming, coding for data acquisition and data manipulation, and specific operational issues related to 鈥渂ig data鈥� analytics. Course material will also cover data privacy, security, and ethical issues.
Terms: Winter 2025
Instructors: So, Hyunji (Winter)
**Due to the intensive nature of this course, the standard add/drop and withdrawal deadlines do not apply. Course Add is the second lecture day.
**No web drop allowed
**Web withdrawal not applicable.
**Web ADD only.
-
INSY 661 Database and Distributed Systems for Analytics (3 credits)
Overview
Information Systems : This course will present the student with many key concepts relating to database technology, how database technology is being used for managing large datasets, and the opportunity to put these concepts to practice. This course will cover database management system (DBMS) concepts, database architecture, database design using entity-relationship (ER) modeling, data storage, file organization, the SQL language, normalization, data integrity, database security, data warehousing, and big data related technologies such as NoSQL, Hadoop, MapReduce, Pic, and Hive.
Terms: Winter 2025
Instructors: Animesh, Animesh (Winter)
**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.
-
INSY 662 Data Mining and Visualization (3 credits)
Overview
Information Systems : The course will teach practical analytics methods and use R (a tool widely used by data analysts) to provide hands on experience on the data mining techniques covered in the class. The focus of the course is on the application of the tools and techniques rather than learning the theory and math behind the models. This course builds upon concepts of data manipulation and coding seen in INSY 660 and covers these tools and techniques in much more depth. Students will be exposed to real world datasets and examples to get hands-experience with making business decisions using dating mining and predictive analytics, and provide R code to apply the predictive models learned in class. At end of this course students will be comfortable using different data mining techniques to solve business problems on their own using R.
Terms: Fall 2024
Instructors: Han, Elizabeth (Fall)
-
MGSC 660 Mathematical and Statistical Foundations for Analytics (3 credits)
Overview
Management Science : This course consists of two parts: (i) The first half of the course focuses on probabilistic and statistical foundations of data analytics. At the end of this part, students will have the mathematical knowledge in following topics: probabilities, random variables, the Central Limit Theorem; prior and posterior distributions, and Bayes鈥� rule; correlation, and Sampling. (ii) The second half of the course focuses on mathematical foundations of decision analytics. At the end of this part, students will have the mathematical knowledge in following topics: linear algebra; calculus of several variables; convexity; separating hyperplanes; unconstrained and constrained optimization; lagrange multipliers.
Terms: Winter 2025
Instructors: Gumus, Mehmet (Winter)
**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.
**No web drop allowed.
**Web withdrawal not applicable.
**Web ADD only
-
MGSC 661 Multivariate Statistical Analysis (3 credits)
Overview
Management Science : The course will begin with the standard linear regressions, and extend to multivariable regression models, factor analysis, principal components, selection models, and dynamic and nonlinear multivariate data methods. Students will be exposed to a broad range of techniques and applications in business analytics through conducting their own statistical analyses.
Terms: Fall 2024
Instructors: Serpa, Juan Camilo (Fall)
-
MGSC 662 Decision Analytics (3 credits)
Overview
Management Science : This course teaches quantitative methods used in business decision making. Topics include: optimization models, optimization under uncertainty, and simulation. Business applications of these techniques are emphasized. Students in this course will acquire expertise in quantitative methods for decision making, through computer analysis of real-life problems.
Terms: Fall 2024
Instructors: Glew, Rob (Fall)
-
ORGB 660 Managing Data Analytics Teams (1.5 credits)
Overview
Organizational Behaviour : In this course, students will learn to: understand barriers to effective work in teams or more broadly in organizations; develop a collaboration style and learn about themselves as team members and leaders 鈥� what are their strengths, what can they improve on; learn how to jointly develop a vision and superordinate goal; develop skills in team communication, using the 鈥榩ower of framing鈥�; build effective working relationships with diverse individuals and groups; become familiar with common organizational functional areas, their analytics perspectives, and their role in cross-functional teams.
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.
**Due to the intensive nature of this course, the standard add/drop and withdrawal deadlines do not apply. Course Add is the second lecture day.
**No web drop allowed.
**Web withdrawal not applicable.
**Web ADD only.
-
ORGB 661 Ethical Leadership and Leading Change (1.5 credits)
Overview
Organizational Behaviour : Students will learn to: excel in the practice of distributed and shared leadership, critical to contemporary business; develop a collaboration style and learn about themselves as leaders 鈥� their strengths, areas for improvement; learn how to jointly develop a vision and superordinate goal; establish guidelines, protocols, and criteria for leading change and for the respectful and ethical collection, storage, and use of data derived from others; develop their capacity to lead across hierarchical levels, including 鈥榣eading upwards鈥�; understand how leadership is necessary for resolving 鈥榳icked problems鈥� (problems that require leadership, not management).
Terms: Fall 2024
Instructors: Saunders, David (Fall)
**Due to the intensive nature of this course, the standard add/drop and withdrawal deadlines do not apply. Course Add is the second lecture day
**No web drop allowed.
**Web withdrawal not applicable.
**Web ADD only.
Complementary Courses (18 credits)
3 credits from the following:
-
BUSA 600 Analytics Internship (3 credits)
Overview
Business Admin : An on-the-job experience in a corporation or organization supervised by an academic faculty member. The learning objectives of this course is to allow the student to put into practice elements that they have learned throughout the program, to gain formal work experience.
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): INSY 660, INSY 661, INSY 662, MGSC 660, MGSC 661, MGSC 662, ORGB 660, ORGB 661
Restriction(s): Students must obtain Instructor鈥檚 or Academic Director approval in writing before registering to this course.
Topics of internship work will vary from employer to employer. Students will need to submit a work proposal to the instructor for approval prior to registering for this course.
-
BUSA 649 Community Analytics Project (3 credits)
Overview
Business Admin : Analytics project in a small-/medium-sized organization focusing on the application of the concepts of real-world analytics problems that organizations without large budgets deal with.Analytics project in a small-/medium-sized organization focusing on the application of the concepts of real-world analytics problems that organizations without large budgets deal with.
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: ORGB 660, INSY 660, MGSC 660, INSY 661, MGSC 661, INSY 662, MGSC 662, ORGB 661.
**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.
15 credits from the following:
-
ACCT 626 Data Analytics in Accounting (1.5 credits)
Overview
Accounting : Exploration of how financial and non-financial metrics can be linked to business performance through practica application learning. Examination of mandatory and voluntary corporate disclosure, financial statement analysis, return predictability, and fraud detection.
Terms: Winter 2025
Instructors: Tan, Hongping (Winter)
-
ACCT 696 Advanced Topics in Accounting Analytics (1.5 credits)
Overview
Accounting : Current emerging topics in accounting analytics. Course content will vary each term.
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.
-
BUSA 611 Independent Studies in Analytics 1 (1.5 credits)
Overview
Business Admin : Procuring of real data to perform a data-centric analysis for an organization or research institution. Under the mentorship of the instructor(s), students will focus their project deliverables on one of the following domains: data management, value proposition, analytic formulation, solution development or user application.
Terms: Fall 2024
Instructors: Hosain, Shoeb (Fall)
Prerequisite(s): BUSA 693, INSY 660, INSY 661, INSY 662, MGSC 660, MGSC 661, MGSC 662, ORGB 660, ORGB 661
Restriction(s): Students must obtain Instructor鈥檚 approval in writing before registering to this course.
Before the instructor agrees to supervise the student, the student must submit a proposal form for approval.
Data Handling Agreement/ Non-Disclosure Agreement must be signed by students
-
BUSA 613 Independent Studies in Analytics 2 (3 credits)
Overview
Business Admin : Procuring of real data to perform a data-centric analysis for an organization or research institution. Under the mentorship of the instructor(s), students will focus their project deliverables on all of the following domains: data management, value proposition, analytic formulation, solution development and user application.
Terms: Fall 2024
Instructors: Hosain, Shoeb (Fall)
Prerequisite(s): BUSA 693, INSY 660, INSY 661, INSY 662, MGSC 660, MGSC 661, MGSC 662, ORGB 660, ORGB 661
Restriction(s): Students must obtain Instructor鈥檚 approval in writing before registering to this course.
Before the instructor agrees to supervise the student, the student must submit a proposal form for approval.
Data Handling Agreement/ Non-Disclosure Agreement must be signed by students.
-
BUSA 684 Analytics Study Trip (3 credits)
Overview
Business Admin : The course will be delivered through a combination of site (company) visits, guest lectures of top-level executives, as well as daily student reflections. It may also be combined with an analytics-related conference held in the location of the visit. Students will be required to study such practices in depth, complete a project related to organizational practice excellence in analytics and write a reflection paper.
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.
-
FINE 675 Financial Valuation Analytics for Startups (1.5 credits)
Overview
Finance : Introduction to finance with an emphasis on analytics, focusing on how the merger of analytics and finance plays a first order role for startups and the decision to accelerate growth.
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): (INSY 660 OR INSY 662 OR Instructor's approval) AND (MGSC 660 OR MGSC 661 OR Instructor's approval)
**Due to the intensive nature of this course, the standard add/drop and withdrawal deadlines do not apply. Course Add is the second lecture day.
**Web ADD only.
**No web drop allowed.
**Web withdrawal not applicable.
-
FINE 695 Advanced Topics in Finance Analytics 1 (1.5 credits)
Overview
Finance : Advanced topics in finance analytics. Content will vary each term.
Terms: Winter 2025
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
-
FINE 696 Advanced Topics in Finance Analytics 2 (1.5 credits)
Overview
Finance : Advanced topics in finance analytics. Content will vary each term.
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): (INSY 660 OR INSY 662 OR Instructor's approval) AND (MGSC 660 OR MGSC 661 OR Instructor's approval)
**Due to the intensive nature of this course, the standard add/drop and withdrawal deadlines do not apply. Course Add is the second lecture day.
**Web ADD only.
**No web drop allowed.
**Web withdrawal not applicable.
-
INSY 669 Text Analytics (1.5 credits)
Overview
Information Systems : Introduction to the basics of text mining and text-based predictions, including leading scripts/packages/libraries like SentiStrength (for sentiment analysis), categorization and classification of a variety of documents. The application of text analytics in solving real-world busines problems.
Terms: Winter 2025
Instructors: Havakhor, Taha (Winter)
-
INSY 670 Social Media Analytics (1.5 credits)
Overview
Information Systems : Methods and tools to leverage the power of social media, with a focus on a variety of questions ranging from strategic to operational matters pertaining to firms鈥� social media initiatives, metrics to capture relevant outcomes, and predictive analytics to link social media chatter to business performance.
Terms: Winter 2025
Instructors: Havakhor, Taha (Winter)
-
INSY 671 Analytics and Open Innovation (1.5 credits)
Overview
Information Systems : This course provides a comprehensive introduction to the use of data analytics in the context of open innovation. Students will draw from existing knowledge from prior courses in the Masters program as well as learn new tools and techniques that can be applied to answer realworld questions about open innovation.
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.
-
INSY 672 Healthcare Analytics (1.5 credits)
Overview
Information Systems : Students will get hands-on experience with real-world datasets to examine how data analytics can be used to predict and understand disease outbreaks, how analytics can be used to improve the operation of hospitals, and the manner in which analytics can be used as decision support for physicians to diagnose and treat patients. By the end of the course, students should be able to develop an appreciation on the changes that are taking place in the provision of healthcare services due to analytics and the role and opportunities for analytics to reduce cost and improve quality of healthcare in their communities.
Terms: Winter 2025
Instructors: Ding, Yichuan Daniel (Winter)
-
INSY 673 Security Analytics (1.5 credits)
Overview
Information Systems : This course provides a comprehensive introduction to data analytics in the context of information security. Students will understand how to leverage data analytics to help in visualizing, detecting, and analyzing information security data. Students will be exposed to real-world datasets and tools and techniques that can be applied to analyze those data.
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.
-
INSY 695 Advanced Topics in Information Systems 1 (1.5 credits)
Overview
Information Systems : Current emerging topics in information systems. Course content will vary each term.
Terms: Fall 2024, Winter 2025
Instructors: Nayebi, Fatih (Fall) Nayebi, Fatih (Winter)
-
MGPO 695 Advanced Topics in Strategy Analytics (1.5 credits)
Overview
Management Policy : Current topics in strategy analytics. Course content will vary each term.
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.
-
MGSC 670 Revenue Management (1.5 credits)
Overview
Management Science : This course will introduce students to revenue management (RM) practices in air transportation, hospitality (hotels, cruises, theme parks, casinos), car rental, media, broadcasting, natural-gas storage and transmission, electricity generation and transmission, and show business (concerts, theaters, sport events). Most applications are recent and made possible by the advances in technology, data and decision analytics. However, there are issues of legality and customer backlash for charging different prices for virtually the same product. The course will touch upon these issues as well. Topics covered include capacity allocation, network management, overbooking, markdown pricing, and customized pricing.
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.
-
MGSC 672 Operations and Supply Chain Analytics (1.5 credits)
Overview
Management Science : The course covers analytical models that explore the key issues associated with the design and management of supply chains. A considerable portion of the course is devoted to data-driven decision models that treat uncertainty explicitly. Topics include supply network design, inventory centralization, value of information, and contracts.
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: (INSY 660 OR INSY 662 OR Instructor's approval) AND (MGSC 660 OR MGSC 661 OR Instructor's approval)
**Due to the intensive nature of this course, the standard add/drop and withdrawal deadlines do not apply. Course Add is the second lecture day.
**During the last week, there will be a make-up class on Thursday, May 28th.
**Web ADD only.
**No web drop allowed.
**Web withdrawal not applicable.
-
MGSC 673 Introduction to Artificial Intelligence and Deep Learning (1.5 credits)
Overview
Management Science : Introduction to deep learning, through its use of neura networks, to learn from data and tasks such as classification, forecasting, data generation. The basis of deep learning up to the applications of the most recent research. Use of deep learning in a production environment, and leveraging techniques such as: Keras, hyperparameter tuning, image classification methods, back propagation, LSTMs, and Autoencoders.
Terms: Winter 2025
Instructors: Borwankar, Sameer (Winter)
-
MGSC 674 Optimization for Data Science (1.5 credits)
Overview
Management Science : Introduction to foundational concepts in optimization with a strong emphasis on applications to problems in data science and machine learning, including fundamental optimization models such as linear, integer, and convex programming, a variety of gradient descent methods, and algorithms ( the expectation-maximization and back-propagation algorithm), as well as the applications to various current and diverse data science and machine-learning contexts
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: (INSY 660 or INSY 662) and (MGSC 660 or MGSC 661) or permission of the instructor
Restrictions: Not open to students who have taken MGSC 695 when the topic was "Optimization for Data Science"
1. The online version of the course includes synchronous and/or asynchronous course activities
-
MGSC 684 Data Driven Decisions and Modelling for Operations (1.5 credits)
Overview
Management Science : Introduction of the concepts, techniques, and tools needed to analyze and improve data-driven modelling to optimize business decisions under uncertainty. Predictive and prescriptive analytic methods are presented to cover the strategies used in practice to address decision-making when information is not well-defined. Exploration of how data-driven and analytical techniques can be used to create value in strategic decisions involving design, management and improvement of operational systems, including the similarities and particularities of different sectors and their link with operations analytic and decision-making.
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 660 or INSY 662) and (MGSC 660 or MGSC 661) or permission of the instructor
Restriction: Not open to students who have taken MGSC 695 when the topic was "Data Driven Decisions and Modelling for Operations"
The online version of the course includes synchronous and/or asynchronous course activities
-
MGSC 695 Advanced Topics in Management Science 1 (1.5 credits)
Overview
Management Science : Current emerging topics in operations management. Course content will vary each term.
Terms: Winter 2025
Instructors: Nayebi, Fatih (Winter)
Prerequisite(s): (INSY 660 OR INSY 662 OR Instructor's approval) AND (MGSC 660 OR MGSC 661 OR Instructor's approval)
**Due to the intensive nature of this course, the standard add/drop and withdrawal deadlines do not apply. Course Add is the second lecture day.
**Web ADD only.
**No web drop allowed.
**Web withdrawal not applicable.
-
MRKT 671 Advanced Marketing Analytics (1.5 credits)
Overview
Marketing : The course will introduce students to advanced marketing analytic techniques available to managers and give them hands-on experience on using these with actual datasets. The major learning vehicle will be lectures with step-by-step exposition of analytical techniques with actual data. These will be then complemented with cases involving data analysis. Topics covered include customer and product analytics techniques.
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.
-
MRKT 672 Internet Marketing Analytics (1.5 credits)
Overview
Marketing : What makes internet marketing different? Introduction to internet marketing - search engine optimization. Inbound marketing - search advertising and privacy concerns. Online tracking and privacy issues.
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.
-
MRKT 673 Pricing Analytics (1.5 credits)
Overview
Marketing : Introduction and basics of price-response functions and pricing optimization. Using data to estimate demand models. Value-based pricing, consumer valuations, personalization. Tactics of price differentiation. Pricing with constrained supply. Team project consultation.
Terms: Winter 2025
Instructors: Haruvy, Ernan (Winter)
-
MRKT 674 Retail Analytics (1.5 credits)
Overview
Marketing : This course will cover the following topics: loyalty program data analysis, assortment planning and category management, market basket analysis, Store location and trade area analysis, and forecasting and buying decision.
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.
-
MRKT 696 Advanced Topics in Marketing Analytics (1.5 credits)
Overview
Marketing : Current emerging topics in marketing analytics. Course content will vary each term.
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.
-
ORGB 671 Talent Analytics (1.5 credits)
Overview
Organizational Behaviour : Learning objectives: to gain experience in collecting and integrating performance and personnel outcome data; to develop and practice skills needed to analyze these types data; to cultivate knowledge and an understanding of the potential and limitations of talent analytics; to become able to apply the skills and knowledge from class to future organizational settings.
Terms: Winter 2025
Instructors: Galperin, Roman; Rubineau, Brian (Winter)
Prerequisite: (INSY 660 OR INSY 662 OR Instructor's approval) AND (MGSC 660 OR MGSC 661 OR Instructor's approval)
**Due to the intensive nature of this course, the standard add/drop and withdrawal deadlines do not apply. Course Add is the second lecture day.
**During the last week, there will be a make-up class on Thursday, May 28th.
**Web ADD only.
**No Web Drop.
*Web withdrawal not applicable.
-
ORGB 672 Organizational Network Analysis (1.5 credits)
Overview
Organizational Behaviour : Learning objectives: to gain experience in collecting and representing organizational network data; to develop and practice the skills needed to analyze network data; to cultivate knowledge and understanding of how social networks are related to consequential organizational outcomes; to become able to apply the skills and knowledge from class to future organizational settings.
Terms: Winter 2025
Instructors: Galperin, Roman (Winter)
-
ORGB 695 Advanced Topics in Organizational Behaviour (1.5 credits)
Overview
Organizational Behaviour : Current emerging topics in organizational behaviour. Course content will vary each term.
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.
