Note: This is the 2019鈥�2020 eCalendar. Update the year in your browser's URL bar for the most recent version of this page, or .
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 study trip 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)
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BUSA 693 Management Analytics Capstone (6 credits)
Overview
Business Admin : Students will work with real companies and organizations on their capstone projects, giving them real world experience to step into the position with confidence. Real-life problems are often multi-disciplinary or multifunctional in nature. Hence, tackling them requires understanding of both management issues and analytical techniques. The topics are selected based on the specific requirements of the capstone projects and will complement and build on concepts previously covered throughout the Masters of Management in Analytics program.
Terms: Winter 2020
Instructors: Hosain, Shoeb (Winter)
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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: Summer 2020
Instructors: Ganju, Kartik (Summer)
**Due to the intensive nature of this course, the standard add/drop and withdrawal deadlines do not apply. Course Add is the third lecture day.
**No web drop allowed
**Web withdrawal not applicable.
**Final exam will take place on September 11, 2020.
**Web ADD only.
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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: Fall 2019, Summer 2020
Instructors: Animesh, Animesh (Fall) Animesh, Animesh (Summer)
**This course will be held on Aug 6, 10, 11, 13, 18, 20, 25, 27 Sep 1, 3, 8, 10, 15 and the final exam will take place on Sep. 18.
**Web ADD only.
**No web drop allowed.
**Web withdrawal not applicable.
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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 2019
Instructors: Khern-am-nuai, Warut (Fall)
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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: Summer 2020
Instructors: Gumus, Mehmet (Summer)
**Due to the intensive nature of this course, the standard add/drop and withdrawal deadlines do not apply. Course Add is the third lecture day
**No web drop allowed.
**Web withdrawal not applicable.
**Final exam will take place on September 25, 2020.
**Web ADD only
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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 2019
Instructors: Serpa, Juan Camilo (Fall)
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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 2019
Instructors: Nasiry, Javad (Fall)
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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: Summer 2020
Instructors: Sonberg, Melissa (Summer)
*This course will be held on August 4, 6, 17, 24 & 31.
**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.
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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: Summer 2020
Instructors: Sonberg, Melissa (Summer)
**This course will be held on August 17, 24, 31, September 2, 4, 9, 11, 14 & 18.
**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:
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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: Summer 2020
Instructors: Hosain, Shoeb (Summer)
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.
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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: Summer 2020
Instructors: Hosain, Shoeb (Summer)
15 credits from the following:
- ACCT 696 Advanced Topics in Accounting Analytics (1.5 credits)
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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: This course is not scheduled for the 2019-2020 academic year.
Instructors: There are no professors associated with this course for the 2019-2020 academic year.
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
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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: This course is not scheduled for the 2019-2020 academic year.
Instructors: There are no professors associated with this course for the 2019-2020 academic year.
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.
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FINE 695 Advanced Topics in Finance Analytics 1 (1.5 credits)
Overview
Finance : Advanced topics in finance analytics. Content will vary each term.
Terms: This course is not scheduled for the 2019-2020 academic year.
Instructors: There are no professors associated with this course for the 2019-2020 academic year.
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FINE 696 Advanced Topics in Finance Analytics 2 (1.5 credits)
Overview
Finance : Advanced topics in finance analytics. Content will vary each term.
Terms: Summer 2020
Instructors: Kondo, Jiro (Summer)
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.
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INSY 670 Analytics for Digital Business Models (1.5 credits)
Overview
Information Systems : Conceptual background coupled with hands -on experience with methods and tools needed to enable digital business models to strategically leverage analytics, with the goal of improving firm performance and decision making, and attaining a competitive advantage.
Terms: Winter 2020
Instructors: Yoo, Changseung (Winter)
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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 2019-2020 academic year.
Instructors: There are no professors associated with this course for the 2019-2020 academic year.
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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 2020
Instructors: Ding, Yichuan (Daniel) (Winter)
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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 2019-2020 academic year.
Instructors: There are no professors associated with this course for the 2019-2020 academic year.
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INSY 695 Advanced Topics in Information Systems (1.5 credits)
Overview
Information Systems : Current emerging topics in information systems. Course content will vary each term.
Terms: Winter 2020
Instructors: Yoo, Changseung; Nayebi, Fatih (Winter)
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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 2019-2020 academic year.
Instructors: There are no professors associated with this course for the 2019-2020 academic year.
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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: Winter 2020
Instructors: Cohen, Maxime (Winter)
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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: Summer 2020
Instructors: Ray, Saibal (Summer)
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.
**Web withdrawal not applicable.
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MGSC 695 Advanced Topics in Management Science (1.5 credits)
Overview
Management Science : Current emerging topics in operations management. Course content will vary each term.
Terms: Winter 2020, Summer 2020
Instructors: Feller, Nicolas (Winter) Serpa, Juan Camilo; Cohen, Maxime (Summer)
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.
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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: Winter 2020
Instructors: Yang, Nathan (Winter)
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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: Winter 2020
Instructors: Yang, Nathan (Winter)
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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 2020
Instructors: Lu, Yi (Winter)
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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 2019-2020 academic year.
Instructors: There are no professors associated with this course for the 2019-2020 academic year.
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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 2019-2020 academic year.
Instructors: There are no professors associated with this course for the 2019-2020 academic year.
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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: Summer 2020
Instructors: Rubineau, Brian (Summer)
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.
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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: This course is not scheduled for the 2019-2020 academic year.
Instructors: There are no professors associated with this course for the 2019-2020 academic year.
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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 2019-2020 academic year.
Instructors: There are no professors associated with this course for the 2019-2020 academic year.
