Skip to Content

MSBAIM Curriculum

As a MSBAIM student, you will focus equally on both technologies and techniques to be prepared for the current and future landscape of business data. Our expert faculty will expose you to various functional areas of business. This program also offers unique treatment of data analytics, gamification, and optimization modeling and significant depth in SAS modeling and usage.

Further, you are able to specialize in areas of interest, such as supply chain.

Your Coursework

To earn a Master of Science degree in Business Analytics and Information Management (MSBAIM), you must complete at least 36 hours of coursework in the following areas:

MGMT 57000: Spreadsheet Modeling and Simulation

In the past eighteen years, Excel spreadsheets have become the standard tool that business people use to model and analyze quantitative problems. The latest versions of these spreadsheet packages contain powerful analytical tools that could be possible only with mainframe computers and mathematically trained personnel more than a decade ago. This course covers up-to-date and practical spreadsheet modeling and simulation tools that can be applied to a wide variety of business problems in finance, marketing, and operations. The topical coverage mainly consists of the following four modules: (1) deterministic and stochastic optimization techniques to determine the best managerial actions under internally- and/or externally-imposed constraints; (2) probability distribution fitting techniques to find the most likely description of the uncertainty in future business; (3) simulation modeling techniques to discover and analyze the risk and uncertainty in business environment and processes; (4) application of spreadsheet modeling and simulation techniques in forecasting asset dynamics (stock price) and pricing options and real investment opportunities. This course provides hands-on experience of computer applications using Microsoft Excel and the spreadsheet add-ins @RISK, RISKOptimizer, SimQuick, etc.

MGMT 57100: Data Mining w/SAS Enterprise Miner

Simon (1977) stated that managerial decision-making is synonymous with the entire process of management. In order to make intelligent decisions, one must have access to data and information. Today’s electronically networked world provides a nearly infinite number of opportunities for data collection. The issue thus becomes: How does one approach these large quantities of data with the purpose of intelligent decision-making? The purpose of this course is to introduce the concepts, techniques, tools, and applications of data mining. The material is approached from the perspective of a business analyst, with an emphasis on supporting tactical and strategic decisions.

MGMT 58200: Management of Organizational Data

This course provides the basic concepts and skills needed to analyze and organize business data, as well as to utilize the organized data to answer a variety of business queries. After successful completion of the course, students will be able to appreciate why database management is important, analyze the data requirements of a business scenario and represent these requirements by means of entity-relationship (ER) diagrams, translate an ER diagram into normalized tables for a relational database management system, and write simple and relatively complex data retrieval commands in the SQL language for Oracle and Microsoft Access databases. The major ideas and techniques will be reinforced through the work on successive segments of a group project. Each student group will also research a current topic in business data management and make a presentation on this topic in class.

MGMT 58500: IT Project Management

Given the increasing complexity of business and technology environments, it is very challenging for project managers to complete mission-critical projects on time and within budget while satisfying clients and stakeholders. This course helps students understand and develop the important body of knowledge and skills in project management by learning useful concepts, frameworks, theories, principles, methodologies, techniques, and tools within the context of IT. Upon completion of this course, they will know the key aspects of a project as identified by the Project Management Institute’s (PMI) Project Management Body of Knowledge (PMBOK) and will be able to effectively manage IT-intensive business projects.

MGMT 59000: Communication and Persuasion

The Communication and Persuasion course enhances student professionalism in business contexts by improving oral communication skills. In this special course designed for MS BAIM students, you will focus on developing and presenting data-driven messages that are professional, clear, concise, and persuasive. By the end of the course, you will develop your ability to:

  • present yourself professionally in diverse business communication contexts (e.g., presentations, group discussions, informal interactions, etc.)
  • explain data and analyses in ways that are clearly understood by receivers
  • provide concise explanations that quickly get to the point without losing important context or content
  • demonstrate mastery at being data-driven by (a) translating data and analyses into a narrative that provides context for your message AND (b) creating informative, clutter‐free data visualizations to support your message
  • make persuasive recommendations that convince receivers to adopt a particular belief or take a course of action

MGMT 67000: Business Analytics

Data analysis and modeling are important skills for effective managerial decision making in business and industry. Advances in technology (computers, scanners, cell phones) have made a significant amount of data available to managers. For example, the Dow Jones Industrial Average is one of the best-known and most widely watched indicators of the direction in which stock market values are heading. Administration and Congressional policymakers rely on statistics for budget decisions and related fiscal policy choices. The Federal Reserve System bases the monetary policy on data analysis. A manager needs to know if the manufacturing process is producing a quality product based on monitoring and assessing process performance. A sales manager has to develop tools to regularly monitor the performance of sales force. A Manufacturer of certain electronic products needs to produce a forecast of future sales in order to decide whether or not to expand production. Banks use customer data to identify and design lucrative banking products. These are a few of the many examples from business where statistics can improve company performance. The techniques learned in this course will help you infer data and as such make better-informed decisions. The course covers basic probability, decision analysis, statistical analysis (hypothesis testing and regression analysis), and simulation and provides an introduction to optimization techniques. Probability models provide tools to handle uncertainty and risk. The statistical analysis focuses on the presentation of data and techniques to draw useful and valid inferences from data. Optimization models and decision analysis focus on techniques that use data to inform decision-making.

MGMT 67200: Advanced Business Analytics w/SAS

The objective of this course is to familiarize you with analytical models and statistical software (SAS and Minitab) that are used frequently in decision making and in empirical study. The focus of the course is on the appropriate means of applying these analytical methods to aid in arriving at decisions. Underlying theoretical concepts are brought forward and demonstrated to understand important methodology. Students are expected to have completed MGMT 670 or equivalent as a prerequisite. The materials in this course are intended to have some initial overlap with the content of 670. The overlap will be used to review fundamental concepts of General Linear Models (Multiple Regression) and introduce you to the analytical software system SAS. While there are a multitude of advanced linear models concepts, this course will focus on model building using (1) Independent Indicator Variables (ANOVA, ANCOVA, Blocking Designs, Factorial Designs, Piecewise Linear Regression, and Splines) (2) Dependent Indicator Variables (Linear Probability Model, Logistic Regression, and Cumulative Logistic Regression), (3) Forecasting and Time Series Models (Autoregressive, Moving Average, ARIMA and Cross-Correlation models), and (4) Volatility Models (ARCH and GARCH, GARCH-M, IGARCH, EGARCH).

MGMT 68300: Management Information Systems

The Internet and other information technologies have reshaped the economic, organizational, cultural and personal landscape. Managers, consultants, and entrepreneurs are all expected to effectively utilize the technology to achieve the organizational goals. Organizations are now expected to not just adapt to technology changes, but also innovate taking advantage of the benefits of the technology and thrive using their new capabilities. Accordingly, the objective of the course is from the perspective of the Information Technology Executive Leadership interested in enhancing the organization’s competitive advantage. Specifically, in the course, we will study in detail what the different types of technologies are, how they can be taken advantage of, and what the critical success factors are for successful implementation of each type. The course material will be delivered by using case-discussions, lectures, and examples.

MGMT 60000: Accounting for Managers

This course is an introduction to Financial Management. As such, the course addresses the two basic financial problems that all companies face: (1) On what should funds be spent (i.e., investment decisions)? and (2) From where should funds be obtained (i.e., financing decisions)? Specific topics include financial statement analysis, financial planning, stock and bond valuation, project analysis (i.e., capital budgeting), estimating the cost of capital, understanding capital structure, and estimating firm value. Readings, case analyses, and problem sets focus on the basic tools used by financial analysts and financial decision-makers.

MGMT 62000: Marketing Management

The objective of this course is to familiarize students with the methods and frameworks necessary to execute strategic plans in a marketing context. Marketing managers must be able to properly identify the needs of their given consumer base and design strategic plans to align the different dimensions of the marketing mix; such as pricing, promotional campaigns, product characteristics, and the necessary distribution channels, while taking into consideration the offerings of the competitors. To this end, we offer an immersive course, which leverages both lectures and case discussions, to enhance the thought process and presentation of hallmark marketing frameworks.

MGMT 63800: Pricing Strategies and Analysis

The course enables participants to formulate a systematic framework for approaching the problem of pricing a product, and more generally, a product line. The concepts and analytical methods necessary to develop such a framework are explored and incorporate marketing, competitive, and legal aspects. The course will use a combination of lectures, case discussions and exercises.

MGMT 65500: Competitive Strategy

Examines how firms obtain and sustain superior returns through the development and implementation of a competitive strategy at the business-unit level. Focus is on strategies that develop and exploit two sources of superior returns: unique value-creating resources (e.g., patents, brand equity, operational capabilities), and powerful positions in markets and supply chains. Participants are expected to be familiar with basic competitive strategy concepts and tools, such as "five-forces analysis", the value chain, and generic strategies. Presents a more analytical perspective of strategy, drawing from game theory.

MGMT 56100: Logistics

Examines the distribution and delivery functions in a manufacturing or service industry. Topics include inventory control in distribution, transportation planning, distribution requirements planning, analysis of waiting lines, distribution system design and facility location and layout analysis. 

MGMT 56800: Supply Chain Analytics

Supply Chain Analytics focuses on data-driven and rigorous decision making in supply chain management. It is a complete problem solving and decision-making process, and integrates a broad set of analytical methodologies that enables the creation of business value.

ECON 61000: Game Theory

An advanced course in game theory and its applications. Among the topics covered are: extensive form games, normal form games, Nash equilibrium, mixed strategies equilibrium, subgame perfect equilibrium, learning and equilibrium, games with incomplete information, repeated games, cooperative games, noncooperative bargaining, and auctions.

MGMT 64200: Portfolio Management

Methods of analysis of common stocks and bonds for individual and institutional portfolios. Review of the empirical evidence of security market efficiency, and implications of that evidence for various methods of security analysis. Team projects to analyze the economy, the particular industry or sector, and selected firms within the industry or sector, and to make specific buy-hold-sell recommendations for the stocks and bonds of those firms.

MGMT 66000: Intro to Operations Management

As goods and services are produced and distributed, they move through a set of inter-related operations or processes in order to match supply with demand. The design of these operations for strategic advantage, investment in improving their efficiency and effectiveness, and controlling these operations to meet performance objectives is the domain of Operations Management. The primary objective of this course is to provide an overview of this important functional area of business.

MGMT 65000: Strategic Management I

Strategic Management is concerned with understanding how organizations might achieve advantage relative to competitors. In particular, it deals with the organization, management, and strategic positioning of the firm so as to gain long-term competitive advantage. To address this issue, we take on the role of general managers, or integrators – that is, managers who make decisions that cut across the functional and product boundaries of a firm. By focusing on what makes managers effective, we shall develop the ability to evaluate different situations and give you usable skills regardless of the business context in which you want to work. Strategic management issues that we will consider include the following: How can my firm create value (e.g., low cost or differentiation; using resources; integrating activities correctly) relative to the competition? How do other players in the industry impact the amount of value I capture from my activities? How can the firm identify new opportunities for value creation and value capture and implement those activities within the firm? How can a corporation create (rather than destroy) economic value through its multimarket activities? What options are available to a firm to successfully diversify?

MGMT 51400: Microeconomics

This course covers microeconomic concepts relevant to managerial decision making. Topics may include: demand and supply analysis; consumer demand theory; production theory; price discrimination; perfect competition; partial equilibrium welfare analysis; externalities and public goods; risk aversion and risk sharing; hidden information and market signaling; moral hazard and incentives; rudimentary game theory; oligopoly; reputation and credibility; and transaction cost economics.

OBHR 66900: Negotiations in Organizations

Decision making examines organizational context, stages, creativity, biases, and group processes. Negotiations examine strategies for preparing and conducting negotiations. The principal focus is on individual and interpersonal aspects of each.

MGMT 61000: Financial Management

This course is an introduction to Financial Management, approached from the view of a general manager. The objective of the course is to provide you with the conceptual and practical framework necessary to evaluate the financial impact of operating decisions. Readings, case analysis, and problem sets focus on the basic tools used by financial analysts and financial decision makers. The course is devoted to the two basic financial problems that all companies face: (1) On what should funds be spent (i.e., investment decisions)? and (2) From where should funds be obtained (i.e., financing decisions)? In this course, we consider such topics as financial statement analysis, financial planning, stock and bond valuation, project analysis (i.e., capital budgeting), estimating and using the cost of capital in practice, understanding the differences among financing alternatives, understanding financing decisions, and estimating the value of an operating business. 

MGMT 57200: Six Sigma & Quality Management

Establishes the link between quality and productivity design and improvement and variance reduction. The course examines some of the more traditional views on quality, as well as those today, which are gaining greater credibility and influence under the umbrella of TQM. It also covers up-to-date and practical spreadsheet modeling tools that can be applied to a wide variety of business problems from finance, marketing, and operations.

MGMT 57300: Optimization Modeling with Spreadsheets

The course emphasizes applications of optimization through cases and computer exercises. The applications are chosen to provide insights into business and economics. Areas covered include linear, network, integer, and nonlinear optimization. At the end of the course, the students should have the ability to model optimization problems work with software to solve optimization problems related to optimization theory in a variety of application settings develop optimization insights into applications in marketing, finance, and operations and get some basic exposure to EXCEL automation.

MGMT 590: Production Scale Data Products

Let's say you have perfected your new algorithm, analysis,  machine learning model, or AI capability. What comes next? In a real world scenario, data science analyses and models need to be turned into scalable data products. In this course, we will learn how to take a data science analysis from a prototype to a product. To this end, we will cover the various ways that analyses are integrated into products (via REST APIs, batch data pipelines, etc.) along with the industry standard workflows for releasing product updates, testing, deployment, and monitoring. The course will also include practical, hands-on components that culminate in students deploying their own AI-driven data product to the cloud.

MGMT 59000: Big Data

There is an exponential growth in the adoption of big data technologies in every walk of life. Organizations are collecting, transforming, storing, and analyzing massive amounts of data. This data is commonly referred to as “big data” because of its large volume, the velocity with which it is collected and transmitted, the variety of forms and formats it takes, and veracity of its origin and content. In order to capitalize on the opportunities presented by big data, this course will cover the following topics: Model Thinking: learn to think in terms of models in order to generate insights into the phenomena under investigation; Visual Analytics: learn visualization techniques using Tableau to query large datasets and gain insights from it; Social Network Analysis: learn how to analyze structure, logic and content of social networks using Gephi; Configuring a Big Data Platform: learn to deploy and use big data technologies such as Cloudera Hadoop on Virtual Box or VMWare; API Programming: learn to use open APIs to collect streaming data from sites like Twitter, Buzzfeed, etc.; and Big data  analytics workflow: learn to create end-to-end big data analytics workflow.

Prerequisites: Familiarity with Intermediate Java will be helpful. However, assignments could easily be completed in Python. We assume no familiarity with Linux and will introduce you to all essential Linux commands. Students need access to a computer with a 64-bit operating system and at least 4 GB of RAM. Note: 8 GB or more of RAM is strongly recommended. 

MGMT 59000: Computing for Analytics

The main goal of this course is to introduce students to the tools and methods for data analytics. The course complements other courses in BAIM program with a programmatic approach of how to retrieve, manipulate, visualize, and analyze the data. The course will focus on challenges associated with large datasets and how algorithms and data structures can aid in resolving some of those challenges. The course will introduce relevant programming techniques in Python.

MGMT 68700: Design: Social Networks & Engagements

Gamification techniques are increasingly becoming popular. The main idea is for firms to use the techniques of game designers to serve objectives as varied as marketing, human resources management, productivity enhancement, training, innovation, and customer engagement. To name a few examples, SAP uses points-based system to encourage carpooling that helps the company save on large gas expenses; at, the Whitehouse encourages innovative solutions through crowdsourcing; and at companies like Google, and Best-Buy, employees participate in information assimilation games called prediction markets providing information to senior managers about ongoing projects.

In this course, you will examine the mechanisms behind designing for human instincts and thereby developing an understanding of their effective use in the modern firm. Gamification is one form of design for human instincts. In order for any design to be effective, it should involve clearly defined strategies and well-managed execution. To identify effective strategies, and metrics for the application of techniques to business, this course will draw upon interdisciplinary source material as well as real-world case studies. It will also identify a number of significant pitfalls to gamification techniques, as well as notable legal and ethical issues, and the problems with implementing radical change in established firms. As a part of this class, you will be designing, playing, and evaluating various games.

MGMT 59000: Predictive Analytics

This course provides a foundational knowledge of predictive analytics used to support businesses. The course will focus on supervised learning techniques for classification such as logistic regression, neural networks, and regression trees. Students will demonstrate their knowledge of the predictive modeling process as they learn various methodologies and implement them on datasets using RStudio and SAS Enterprise Miner.

MGMT 59000: Spreadsheets & Macro Programming

In this course, students will gain exposure to the basics of spreadsheets and related advanced topics. In particular, students will learn programming (using tools such as Visual Basic for Applications) to design functions and macros that will enhance spreadsheet models. It will demonstrate the use of these enhanced features in a variety of business settings with examples from finance, marketing, and operations. In addition to in-classroom time, this course may also meet in computer-based labs for hands-on instructions and implementation.

MGMT 59000: Using R for Analytics

This course exposes students to RStudio and the R programming language as tools for data analytics. Students will develop a small portfolio of projects that demonstrate fundamental knowledge of programming, study reproducibility, data reshaping, exploratory data analysis, data visualization, and basic predictive modeling techniques such as regularization and shrinkage using R.

MGMT 59000: Web Data Analytics

This industry-agnostic course is focused on training leaders to be able to talk to and manage the people who are collecting data and are making inferences from the data, and then make data-driven decisions. It will cover tools to collect, manipulate, and analyze data from the web and other sources, with the objective of making students data-savvy and comfortable with deriving insights from real-world, large datasets. Students will be exposed to the power of clickstream analysis and the possibilities that can be unleashed from testing and experimentation. The emphasis of the course will be on data savviness and practical usefulness.

MGMT 68200: Digital Business and Information Strategies

The Internet and other emerging technologies have enabled new ways for companies to organize their businesses. Companies are also increasingly dealing with digital information that is different in many ways from other goods and services. The purpose of this course is to explore how new digital business models and digital information affect company strategy, market structure, and pricing. It will articulate the digital strategy of an organization and align it with the overall strategy using critical thinking.

Mini cases about digital products will be conducted, related to:

autos --> driverless vehicles; cash --> BITCOIN; fundraising --> crowdfunding; delivery of goods --> DRONE delivery; health --> e-health. Artificial Intelligence (AI), Virtual Reality (VR), and Ad Blockers will also be introduced.

The course examines topics such as pricing and competition on the Internet, cross-channel competition and marketing, “Long Tail”, network effects, platform, dynamic and usage-based pricing. These issues will be illustrated via Facebook, Google, Uber, Airbnb, Apple, and cases. How these concepts lead into strategic advantage will be demonstrated.


MGMT 58600: Python Programming 

The course is an introduction to the Python programming language and its applications in business settings. Lectures will be problem-driven and mostly group-work based. Students will gain hands-on experience with a wide range of business problems. The focus of the course is to learn the basic elements of Python as a foundation for advanced topics such as data analytics. The main purpose is to develop the ability to write programs to solve real-world business problems. In addition to in-classroom time, this course may also meet in computer-based labs for hands-on instructions and implementation. 


MGMT 59000: Analyzing Unstructured Data

This course aims to prepare master students with the necessary tech for analyzing unstructured data. The course fills in the technical gap between the traditional analysis of structured data and the requirement for more advanced analysis on unstructured data. With that being said, this course requires students to have a prerequisite of data analysis on structured data, e.g. data mining and python implementation. After taking this course, students are expected to be capable of collecting, processing, and analyzing online unstructured data using the mainstream open-sourced software, e.g. Python. Due to the limited time, we take text and image as examples for illustration. The course is formatted as a combination of seminars and hands-on coding practices in class. Students are expected to code and debug in the class. The main topics we will cover in this course include:

  • Use Python to collect unstructured (text) data
  • Use Python for descriptive unstructured data analysis
  • Use Python for predictive unstructured data analysis

Prerequisites: MGMT 58600: Python Programming and MGMT 57100: Data Mining w/SAS Enterprise Miner.

MGMT 69000: Industry Practicum 

MGMT 59000: Predictive Analytics ELI Project 

Students may select 5 credits of electives to suit their individual interests.

This program starts with a summer session and spans 11 months. Many courses will be combined with other master’s programs to ensure you develop skills to work in cross-disciplinary teams and across functional boundaries.

MBA degree holders can request waivers for Business Foundation courses they have taken previously. All waivers must be approved by the academic director of the program.

View the MSBAIM sample curriculum (subject to change).

For a searchable directory of courses visit Purdue's online Course Catalog.