Course Descriptions

MSBA 5002: Python Programming

Python is one of the most in-demand programming languages on the market today and is used in a variety of industries, particularly in data science and the machine learning domain. In this two-week practice-oriented coding boot camp, we will examine basic elements of programming in Python to allow learners to gain coding knowledge and proficiency within a short time. Specifically, students will develop a solid understanding of Python syntax, including the key language rules and operations. We will also introduce the basic data analysis process of wrangling, exploring, analyzing, and communicating data using libraries like NumPy and Pandas.

MSBA 5003: Statistics Foundations

This part of the bootcamp is designed for students to gain a solid grasp of statistical analysis and modeling. This will also form the foundation for more advanced topics to come in later courses. The course will emphasize the principles of statistical reasoning, underlying assumptions, hypothesis testing, and careful interpretation of results. Topics include data presentation and summarization, regression analysis, fundamental probability theory, random variables, introductory decision analysis, estimation, confidence intervals, hypothesis testing, and ANOVA.

MSBA 5011: Power Skills

Power skills, which are personal attributes that enable us to interact effectively and harmoniously with other people, play a significant role in working and interacting with the people around us effectively. This bootcamp is packed with tips, tricks, and information geared to help students convey effective communication through writing and presentations. Specifically, students will enhance their understanding of key concepts, and gain tools that are critical to their future careers.

MSBA 5012: Excel Foundations

As one of the most powerful applications ever built, with a massive and widely underappreciated feature set, Excel plays a crucial role in the data analysis toolbox and has been widely used in the business world. This portion of the boot camp is designed to ensure that students have sufficient knowledge in data preparation and manipulation in Excel. They will also gain hands-on experience in using Excel to enhance informed business decision-making.

MSBA 5000: Accounting Basics

In this introduction to the financial reporting process, study emphasizes the accrual basis of accounting. Students learn to interpret income statements and balance sheets, analyze business transactions, and determine the effects of transactions on assets, liabilities, and equity.

MSBA 5001: Finance Basics

This course introduces the fundamental concepts and techniques of finance and might be subtitled “what every business major needs to know about finance.” It is designed to provide students a foundation with regard to the key concepts from each of three major areas of finance — investments, financial markets and corporate or managerial finance. In the class, we will discuss issues relating to the financial markets, the time value of money, financing, valuation, investments, and other topics.

MSBA 6605: Data Driven Analytical Models

Stated broadly, this course is designed to introduce students to modern data driven modeling building upon the preparatory work done in the summer boot camp and prior preparation in basic statistics, linear algebra/calculus, and programming. This is an introductory and overview data analytics course with a focus on understanding the conceptual foundations of data driven model building with more detailed and deeper treatment of techniques being covered in subsequent courses in the sequence. Students will learn about descriptive techniques and predictive analytics on structured data. Students will implement these techniques in Python and course material will include additional features of the Python language that are essential for implementing these techniques. (3 credits)

MSBA 6615 Information Storage and Data Visualization

Data has become a core strategic asset to gain and maintain a competitive advantage for today’s business. As a result, data analytics, the process of transforming data into actionable insights, has a profound impact on corporate decision-making and strategies. In this course, students will not only explore various data analytics models and their business applications but also innovative data storage techniques. Particularly, students will gain hands-on experience and develop in-demand skills using information visualization tools (e.g., Python, Tableau, and D3.js) and database management systems (e.g., SQL, NoSQL, and big data management systems). (3 credits)

MSBA 6620 Business Data Mining & Machine Learning

This course will provide a more comprehensive and in-depth coverage of predictive modeling with an emphasis on modern data mining and machine learning approaches such as tree ensemble methods, neural networks, and support vector machines that are most used in industry. Students will also be introduced to the basics of deep neural networks and their application to image recognition and natural language processing. Students will learn about techniques and their practical implementation through hands-on work in Python and the course material will include additional features of the Python language and machine learning libraries as required. Students will also learn about how to choose the best or most appropriate predictive model for a business problem at hand, considering predictive model performance assessment and the business context. (3 credits)

MSBA 6650 Responsible Analytics: Data Security, Ethics, and Governance

Data-informed decision making has created new opportunities, but also expands the set of prospective risks to organizations. One of these risks comes from grappling with the “should we?” question regarding data and analytics, and associated privacy concerns. In this course, we will explore a few frameworks to address the issues related to the proper roles of public law, government regulation, and ethics in performing and managing analytics activities. The course will cover applicable theory, guidelines, and recent examples, and make use of case studies. (3 credits)

MSBA 6100 – Business for the Greater Good

This course examines the interaction of business, government, and society with a specific emphasis on how businesses create value for their stakeholders. This course utilizes a stakeholder theory lens to explore the role of markets and market failure within society, the expectations of modern corporations, and how businesses design value propositions that respond to and balance the needs of all stakeholder groups while maintaining financial viability. Students will utilize current case studies and simulations to explore how businesses navigate and respond to existing and emerging issues that require a balance between social, environmental, and economic resources with emphasis on corporate social responsibility, triple bottom line accounting, ethical decision making, and innovation to address market failures. (3 credits)

MSBA 6230 Principled Leadership

This course explores the concept of Principled Leadership which involves leading people using methods that adhere to the values of the leader and the leader’s organization. Students in the course will examine a diverse roster of leadership approaches and critically evaluate how these approaches may align with their values, the current demands of business, and the values of different business organizations. Students will support their leadership development by exploring specific management topics in motivation, team building, organizing, decision making, and managing employee job performance and job attitudes. (3 credits)

MSBA 6270 Applied Marketing Management

This class introduces the concepts and principles of marketing management. The primary thrust of this course is framework-based analysis of marketing problems. The goal of the class is for students to learn the basics of marketing management, as well as improve their structured thinking, communication and analytic skills. The course emphasizes the following: Primary and changing perspectives on marketing management in the New Economy; the impact of interactive media on marketing management, applied marketing management and strategy, domestic and global, an international focus in developing marketing management and strategy. (3 credits)

MSBA 6450 Project Management

The purpose of this course is to provide an overview of the knowledge, skills and processes associated with project management as it is practiced in a wide variety of organizations. This course is appropriate for individuals with limited project management knowledge/experience, as well as those who have extensive experience managing projects in organizations for internal and/or external clients. The course will cover project initiation, planning, execution, monitoring and controlling, and closing, and will focus on building subject matter knowledge in the project management discipline. Additionally, this course will provide students with opportunities for skill building using project management tools, techniques, and software (e.g., MS Project and Oracle® Crystal Ball). Additional guidance will be provided for individuals who seek PMI project management certification (CAPM® or PMP®). (3 credits)

MSBA 7170 Financial Management

Selected topics in corporate finance including the finance function and the role of financial managers in a firm, capital structure optimization, project selection methods, shareholder payout policies and corporate governance. (3 credits)

MSBA 7150 Quantitative Decision-Making with Accounting Data

In this course, students delve into how leaders use cost and revenue data for decision-making, planning, and control. The course focuses on quantitative analyses for managerial decisions using accounting information. It covers qualitative and quantitative data aspects, sources, critical thinking, mathematical models, problem-solving, and effective communication of recommendations, ethical considerations, and the impact of decisions. (3 credits)

MSBA 6660 – Deep Learning for Business

This course will introduce advanced machine learning and deep learning techniques with a special focus on their implications for business decision-making and strategies. We will examine how deep learning helps empower data analysis, especially unstructured data analysis, using natural language processing (NLP) and computer vision. We will cover core concepts in modern AI and deep learning by introducing various techniques, including convolutional/recurrent neural networks, distributed representations, language models, generative models, and attention and transformers. Importantly, we will put deep learning into the business context and explore its practical applications in various business domains, including marketing, finance, media, retail, healthcare, etc. (3 credits)

MSBA 6610 – Business Forecasting and Decision Models

This course will cover the most important data analysis techniques and prediction techniques of time series analysis and their practical business applications, using realistic data and business cases with a primary focus on demand forecasting methods. The course will also discuss how expert judgment and statistical and machine learning-based forecasts are used in collaboration to achieve practical business outcomes. We will then focus on the development of decision models and their application to management problems. Specific topics covered in this course include fundamental techniques such as linear programming, integer linear programming, and network optimization models. Realistic business cases will be chosen from a variety of industries and emphasize risk and scenario analysis in the presence of uncertainty, especially when decision models rely on forecasts and other estimation techniques. (3 credits)

MSBA 6670 Essentials of Marketing Analytics

This course is tailored to provide an understanding of important marketing concepts and their application in today’s digitally driven, data-rich world. The course explores the intersection of marketing strategies and data analytics, allowing students to make informed, evidence-based marketing decisions. Throughout the semester, students will explore key marketing concepts such as customer segmentation, targeting, positioning, and branding, as well as gain exposure to the nuances of customer behavior, customer lifetime value, and customer journey analytics. This theoretical knowledge will be underpinned by a practical understanding of various analytical tools and techniques used to analyze and understand market data. By the end of the course, students will be adept at using sophisticated data analytics tools to inform marketing strategies, measure performance, and optimize marketing efforts for enhanced customer engagement and business growth. (3 credits)

MSBA 6675 Essentials of Supply Chain Analytics

Supply chain analytics involves the development of insights and data driven decisions using data gathered on all aspects of a supply chain – procurement, supplier relationships, production, distribution, and transportation, as well as related marketing activities such as customer segmentation for demand and sales generation. The course will begin with an overview of supply chain architectures over a variety of industry domains and then focus on a few specific areas of data driven decision making in supply chains such as demand forecasting, inventory management, and distribution logistics. Students will also learn about how uncertainty and its estimation play a vital role in designing robust supply chains using a supply chain simulation game. The course will then discuss how logistical problems in the distribution phase of the supply chain can be addressed through network optimization techniques. (3 credits)

MSBA 6680 Financial Industry Analytics

With the increasing prevalence of financial data and machine-supported financial transactions, the ability to understand, analyze, and solve problems from data has become increasingly important in the financial area. This course will introduce methods and tools that have been widely used in decision-making in the financial industry, which may from time to time include macroeconomic event studies, analysis of term structures, equity data analysis, style analysis, credit risk, extreme value analytics, trading analytics, volatility measurement, portfolio management, and enterprise risk management. (1.5 Credits)

MSBA 6685 Healthcare Analytics

With the increasing adoption of electronic health record systems, the ability to understand, analyze, and solve problems from data has become increasingly important in the healthcare area. Big data analytics is becoming central to the healthcare industry, both regarding delivering effective outcomes and controlling escalating costs. In this introductory course designed for healthcare analysts and IT professionals, Students will build foundational skills and knowledge in healthcare data analytics. Students will explore the value proposition for clinical intelligence and the role of analytics in supporting a data-driven healthcare system. They will apply knowledge and skills from healthcare data mining, data science, machine learning, AI, and data management to address practical healthcare business and clinical intelligence issues. In addition, the topics covered in this course will provide the foundation for a future advanced deep learning for healthcare course. (1.5 Credits)

MSBA 6690 Sports Analytics

The class will discuss the theory, development, and application of analytics in sports. Students will learn about the application of analytics in sports for purposes of in-game strategy, player performance, team management, sports operations, and fantasy competitions, among many other topics. The class will consist of lectures, and guest speakers from the sports industry, and culminate with a group project. (1.5 Credits)

MSBA 6820 Professional Development

An effective job search requires a tactical routine, a prioritization process, a well-defined order of specific tasks, a targeted marketing program, and a measurement criterion to help ensure that students are optimizing their time and ability to track progress. This professional development workshop series will introduce available resources and present requirements for current analytics jobs. In addition, we will also pack with tips, tricks, and key information to help students develop the required skills, build a strong resume, apply for jobs more effectively, build a strong network, and eventually succeed in their career and professional development. (1 Credit)

MSBA 6985/MSBA 6998 Capstone

Every MSBA student is required to complete a Business Analytics Capstone before graduation. Students can choose one of three options to fulfill this requirement: (3 semesters, 2 Credits in total)

1. Conduct a research project with one of the business analytics faculty members. (MSBA 6998)
2. Complete a business project/internship with the Center for Organizational Analytics. (MSBA 6985)
3. Complete a data analytics internship (minimum 8 weeks) with an external industrial or non-profit organization. (MSBA 6985)

Students will be advised to meet with the Director of the MSBA Program at the beginning of the Fall semester to discuss the specific timeline and requirements.