Creating High Performance Teams

Creating, leading or contributing to a high performance team are critical skills for managers today. This introductory module helps you build an understanding of the key elements of a high performance team, and what leads to team effectiveness. During the module, students are led through a set of practical sessions that reveal a five-step process for building high performance teams. The knowledge gained and the skill set developed are immediately transferable to the work place.

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Predictive Modelling

The course will combine three key elements: analytics techniques, business applications, and basic coding/programming with emphasis on applications to various business cases. The course will cover 2 major topics within the domain of predictive analytics: “predicting quantities” and “predicting events”. Within the “quantities” part we will focus on linear models, variable selection and regularizations, as well as on time-series analyses. Within the “events” part we will focus on generalized linear models (logistic regression) and get an introduction to supervised machine learning (CART, random forest, boosting, and neural networks).

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Machine Learning & Artificial Intelligence

This course will introduce machine learning (ML) concepts, with a heavy focus on business applications. The course will look in-depth at all three types of ML: supervised (including classification and deep learning), unsupervised (including association rule learning and dimensionality reduction), and reinforcement learning. The course will survey key technologies and applications that are driving the ML revolution. The course will include some theoretical background, but will be application-focused. The overall goal of the course is to provide a foundation and framework for understanding how to use machine learning models in data-driven decision making.

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Introduction to Management

This course introduces the main functional areas of business, including strategy, marketing, operations and finance, and demonstrates how these areas interact to produce and market products and/or services effectively and efficiently. It provides an overview of the modern corporate enterprise in Canadian and international contexts, and of the tasks, practices, and responsibilities of its managers.

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Introduction to Analytical Modeling

The course will establish a foundation of statistical modelling techniques to be immediately useful for analysis and to provide a foundation for more advanced material studied throughout the program. Topics will include data types, random numbers, probability models, hypothesis testing and statistical inference, and a thorough grounding in simple and multiple regression. The course is designed to ensure that all students, regardless of background or experience, are proficient in the use and application of a variety of statistical methods.

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Acquisition and Analysis of Data

This course will focus on the data management techniques frequently used as a precursor to analysis with ‘real world data’. Topics will include including database structures, SQL, data cleaning, merging and filtering, detecting and correcting errors. The course will also cover the application of visualization to developing and telling stories with data with data visualization techniques.

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Marketing Analytics

This course deals with aspects of the collection and use of consumer/customer information for the purpose of making marketing decisions. Through a hands-on approach, the course provides the skills necessary to understand and employ basic analytics to translate market-related information into specific operational plans in various marketing decision contexts. Approaches covered in this course include a variety of marketing analytics including those related to consumer choice, consumer preference, market response, market segmentation, and positioning.

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Analytical Decision Making

This course deals with aspects of the collection and use of consumer/customer information for the purpose of making marketing decisions. Through a hands-on approach, the course provides the skills necessary to understand and employ basic analytics to translate market-related information into specific operational plans in various marketing decision contexts. Approaches covered in this course include a variety of marketing analytics including those related to consumer choice, consumer preference, market response, market segmentation, and positioning.

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Big Data Analytics

The course will cover big data architectures, the Hadoop ecosystem (especially Spark), NoSQL databases, and a sampling of powerful applications of big data analytics, including recommender systems and social network analytics. New concepts will include additional applications of big data analytics, including text and unstructured analytics, such as sentiment analysis, document clustering, and document classification.

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Operations and Supply Chain Analytics

In this course, we explore analytical issues in manufacturing and service operations, with particular attention to global supply chains. Specific concepts, decisions, and quantitative techniques commonly encountered in the management of operations and supply chains are emphasized. We also study strategic and tactical perspectives and highlight the competitive advantages that effective and efficient operations can provide for an organization. The course includes three modules: Controlling Operations Systems, Designing Operations Systems, and Integrating Operations Systems. Class time focuses on the key analytical concepts of each topic, and on the applications of this material in decision making within the operations function.

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Project Management

This course covers concepts in the four basic functions of project management (planning, organizing, directing, and controlling) from a leadership perspective. A core focus in the course is learning how to create and drive an effective project environment within a company culture, and what can we do as leaders to ensure the organization launches and delivers projects well every time. The course provides students with twenty-three instructional hours, which they can apply to certification requirements for either a Certified Associate in Project Management (CAPM), or (with additional training) a Project Management Professional (PMP) with the Project Management Institute (PMI).

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Advanced Analytics Using SAS Enterprise Miner

The best way to achieve a working knowledge of commercial-grade business analytics systems is to gain familiarity with at least one such system. And the SAS system is a major provider of business analytics software. This course will help attendees gain a complete understanding of how SAS software works and is used and will facilitate learning any other systems that they may encounter in their work lives. The course will prepare you for the SAS Certification exam.

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High Performance Teams

This class builds on the work that was done during the first residential session.

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Analytical Decision Making

In this course, we explore the use of analytical methods in management problem-solving, highlighting organizational and contextual issues. We study how to construct an analytical model of a problem that can be manipulated or solved to identify a decision that yields the best outcome, according to one or more carefully defined criteria. The challenges of communicating and implementing results in an organizational context will also be explored through mini-cases and illustrations.

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Multivariate Statistical Analysis

In this course we study multivariate statistical methods and how they are used in management analytics. After a review of multivariate distributions, sample geometry, and general linear models, we focus on important approaches to multivariate statistical analysis such as: categorical data analysis; multi-equation regression; principal components; classification methods; cluster analysis; and multidimensional scaling.

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Analytics in Financial Markets

This course provides a comprehensive overview of derivative instruments and the markets in which they are traded. We develop the key relationships employed by practitioners to value derivatives and illustrate how they are used to manage risk and/or to enhance investment yields. The course covers plain-vanilla derivatives such as futures, forwards, FRA’s, swaps, and options, as well as more recent innovations like exotic options and credit derivatives. We also explore best practices in market and credit risk management as well as recent developments in the regulatory environment.

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Pricing Analytics

Pricing and Revenue Optimization (PRO) focuses on how a firm should set and update pricing and product availability decisions across its various selling channels in order to maximize its profitability. Through a combination of case studies, lectures and guest speakers, this course reviews the main methodologies of analytical pricing and surveys current practices in different industries. Within the broader area of pricing theory, the course places particular emphasis on tactical optimization of pricing, capacity allocation decisions, demand forecasts, market uncertainty, and the tools of constrained optimization.

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Management of Analytics

This is a capstone course that ties together the key concepts of the program and links them to the strategic objectives of organizations. Topics include: Supply Chain Management; Service Management; Innovation; Managing Change; Ethics and Analytics. We will also discuss senior management strategies for developing and using analytical expertise in organizations. An integrative case exercise is a key part of this module.

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MasterCard Innovation Challenge

Students will be presented with transactional data. Teams will then use this information, along with their own ideas and creativity, to create a potential product that could be developed based on this data.

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Data Privacy Workshop

An expert in data privacy will discuss Canadian privacy obligations and compare these to American, Asia-Pacific, and EU practices. Students will learn about database governance as well as international consumer privacy and data protection policies.

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Entrepreneurship & Innovation

This course introduces students to entrepreneurship and innovation, designed to embed a much greater appreciation for the role of entrepreneurial thinking and know-how in the minds of all students, regardless of current or desired role in business – start-up or corporate innovation. The course will provide a unique opportunity for students to immerse themselves in what it means to be entrepreneurial, and in the entire new venture context. Students will finish the course with the following:

  • Ideation techniques such as Design Thinking
  • The ability to differentiate, using a systematic and thorough approach, between an idea and a true business opportunity, the ability to assess an analytics-based new business venture or corporate innovation
  • The ability to understand what strategies and resources are required and available to translate a viable opportunity into a real business
  • The ability to 'pitch' a business opportunity in order to gain whatever resources are necessary to execute on the opportunity presented
  • An appreciation for various types of analytics based new ventures and innovations
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Text Analytics

80% of all corporate data is captured in an unstructured textual form. A billion Tweets are sent every two days. Americans spend 54 billion minutes per month reading and writing Facebook status updates. In this course, we will explore the use of text analytics to organize, understand, and mine textual data sources. We will investigate tools and techniques for preprocessing (e.g., removing noise from) unstructured textual data sources; tokenizing text streams; named entity recognition and part-of-speech tagging; sentiment analysis; text classification; and information retrieval. We will focus our discussion on the practical application of these techniques, especially in the case of social media monitoring.

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Analytics Strategy & Change

This course covers the role strategy development and change management play in successfully capitalizing on the promise of Analytics. The course provides students with the opportunity to synthesize their learnings and understand what to change and how to do it. The course integrates 2 complementary aspects of driving organizational success through analytics – what to do (the strategy piece) and how to make it happen (the change management piece). The course covers the entire spectrum of enterprise strategic and cultural transformation, including functional level changes in strategy (e.g. marketing, finance) through to enterprise/corporate level changes to strategy and culture. The course also touches on strategy and change as they relate to intra- and entrepreneurial endeavors

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Curriculum

The program curriculum has been developed to provide the team skills, business acumen, analytic capabilities, and communication skills you will need to be successful. It includes extensive review of the fundamental mathematical and statistical theories and methods that underlie modern analytics…but with a practitioner focus.

Students will be exposed to a variety of tools & programming languages throughout the MMA program including SAS, R, Python, Tableau, Hadoop, and Spark. Students are encouraged to participate in optional workshops in which they will be introduced to these tools. These sessions will take place outside of regularly scheduled classes. Additional self-study will be required in order for students to master these technical skills.

Residential Session 1
(Kingston one week)

Module 1 (Toronto)
Module 2 (Toronto)
Residential Session 2: Electives
(Kingston one week)

Select one of:

Module 3 (Toronto)
Module 4 (Toronto)
Module 5 (Toronto)
DataCamp Logo

As part of the program, students will have access to DataCamp for the first 6 months. DataCamp is an interactive learning platform for data science. Learn R & Python from the comfort of your browser with over 75+ courses featuring high-quality video, in-browser coding and gamification. Courses are taught by experts and range from importing data, data visualization, machine learning, deep learning & more.

Professional Designations

During the program, you will receive training that can be applied for a Certified Analytics Professional (CAP) with the Institute for Operations Research and the Management Sciences. Learn more

The program also provides twenty-five instructional hours which can be applied to the certification requirements for either a Certified Associate in Project Management (CAPM), or (with additional training) a Project Management Professional (PMP) with the Project Management Institute (PMI).

As part of the program, you will also take the SAS Certified Predictive Modeler (using SAS Enterprise Miner).

SAS logo
Jerry Oglesby

We are pleased to be working with the Smith School of Business and their Master of Management Analytics program. I believe that graduates of this program will be in great demand 

Jerry Oglesby
Senior Director, Global Academic Program & Global Certification
SAS