Business Analytics Course Descriptions

MSBA 6111: Business Essentials for Analytics Professionals

Introduction to fundamental concepts and applications in core business disciplines such as financial accounting, marketing, operations, and strategy. The course emphasizes how data and analytics can be used in these domains to drive value and innovation using a series of real-world business analytics applications from different domains. The course aims to increase students’ business acumen and allows them to effectively partner with key functional areas of an organization.

MSBA 6121: Introduction to Statistics for Data Scientists

This course is designed to develop statistical thinking, i.e., understanding variation and using data to identify possible sources of variation. Specific techniques include basic descriptive and inferential procedures and regression modeling. The emphasis is on understanding such analysis for their relevance to decision making.

MSBA 6131: Introduction to Business Analytics in R

Introduction to key processes, building blocks, and use cases of business analytics through R, including data acquisition, engineering, visualization, basic concepts of exploratory and predictive analytics, and lifecycle of business analytics projects.

MSBA 6311: Programming for Data Science

According to recent industry surveys, Python is one of the most popular tools used by organizations for data analysis. We will explore the emerging popularity of Python for tasks such as general-purpose computing, data analysis, website scraping, and data visualization. You will first learn the basics of the Python language. Participants will then learn how to apply functionality from powerful and popular data science-focused libraries. In addition, we will learn advanced programming techniques such as lambda functions and closures. We will spend most of our class time completing practical hands-on exercises.

MSBA 6321: Data Management, Databases, and Data Warehousing

Fundamentals of database modeling/design, normalization. Extract, transform, load. Data cubes/setting up data warehouse. Data pre-processing, quality, integration/stewardship issues. Advances in database/storage technologies.

MSBA 6331: Big Data Analytics

The course covers the utilization of big data tools, cloud computing platforms, and MLOps practices to efficiently process, manage, and analyze massive datasets, emphasizing the development of robust data pipelines and the deployment of machine learning operations for real-world applications. Students gain practical experience in harnessing the power of distributed computing frameworks, scalable data storage and processing tools, and cloud services to address the challenges posed by the growing volume and complexity of contemporary data science. Topics include: Hadoop MapReduce, Hive, Spark, Streaming Analytics, Cloud Computing, NoSQL, and MLOps.

MSBA 6341: Responsible AI

In an era where artificial intelligence plays an increasingly pivotal role in business analytics, responsible AI practices are imperative. This advanced course will equip students with the knowledge, skills, and ethical mindset needed to develop AI solutions that are not only technologically proficient but also responsible, fair, and transparent. It covers topics such as ethical AI, algorithm fairness and bias mitigation, and explainable AI.

MSBA 6351: Time Series Analysis and Forecasting

A wide variety of data science tasks, ranging from financial stock market trading to inventory management to sales planning, requires understanding time trends and issuing time forecasts. These types of tasks leverage repeatedly measured data records across a span of time, called time series. In this course, we will introduce techniques for time series analysis and forecasting and their applications in business settings, including thorough discussion of canonical ARIMA models and a brief introduction to deep-learning-based models such as recurrent neural networks and transformers.

MSBA 6355 Building and Managing Teams

Examine individual, group, and organizational aspects of team effectiveness; learn and practice basic skills central to team management; develop appreciation for team leadership function; learn the tools for effective team decision making and conflict management; develop general diagnostic skills for the assessment of team issues within and across organizations and national boundaries.

MSBA 6335: Effective Communication for Analytics Professionals

In today's data-driven business landscape, the ability to communicate complex analytical insights effectively is paramount. This specialized course is tailored for Master of Science in Business Analytics students, equipping them with the essential skills to convey data-driven findings with clarity, impact, and persuasion. It covers topics including data storytelling, visual communication, presentation techniques, and stakeholder engagement strategies.

MSBA 6411: Exploratory Data Analytics

This course introduces the fundamentals of exploratory business analytics. Students will learn to detect relationships and patterns in both structured and unstructured data via a variety of exploratory techniques such as data visualization, clustering, dimensionality reduction, probabilistic graphical models, anomaly detection, deep neural networks, and generative AI. The course integrates theoretical discussion and hands-on practice using Python, with an emphasis on real-world problem-solving and effective technical/managerial communication.

MSBA 6421: Predictive Analytics

Fundamentals of predictive modeling and machine learning, assessing the performance of predictive models: logistic regression, decision trees, naïve Bayesian classifiers, support vector machine, ensemble learning, deep neural network, and their applications in structured and unstructured data.

MSBA 6441: Causal Inference via Econometrics and Experimentation

Controlled experiments in business settings, experiment design, A/B testing. Specialized statistical methodologies. Fundamentals of econometrics, instrument variable regression, propensity score matching.

MSBA 6345: Consultative Problem-Solving and Agile Management for Analytics Projects

Consultative problem-solving techniques, including using collaborative frameworks to bring strategic thinking skills to analytics projects. Project management skills with a focus on the Agile mindset and the implementation of Scrum practices.

MSBA 6451: Prescriptive Analytics for Optimal Decision Making

This course explores optimization techniques in business analytics, providing students with the skills to formulate, solve, and interpret prescriptive models for optimal decision-making, resource allocation, and process improvement in complex organizational settings.

MSBA 6461: Advanced AI for Natural Language Understanding

This course covers several topics in natural language understanding using machine learning and artificial intelligence. Students are introduced to foundational natural language processing techniques (e.g., text pre-processing and bag of words representation) and more advanced topics in natural language understanding, such as representation learning, sequential models, transformer models, and large language models (e.g., ChatGPT), along with their business applications. The course combines theoretical discussions of concepts and techniques and hands-on practices in Python, leveraging popular packages such as Tensorflow or Pytorch. The overall objective is to develop a foundation for understanding and leveraging modern AI tools and techniques for language-understanding.

MSBA 6155: Generative AI for Business Applications

Generative AI will give students an understanding of the transformative paradigm of Generative AI - its applications, limitations, ethical and social implications, and how it can unlock previously inaccessible value. This course is designed to prepare students for the generative AI related choices they will face as leaders and managers. Through this course, students will develop a robust understanding of the technology and an experience in working with popular generative AI tools such as ChatGPT and Midjourney.

MSBA 6431: Recommender System Techniques and Applications

With the fast evolution of machine learning and the advent of generative AI, the development of recommender systems is greatly enhanced and their applications in online platforms are becoming imperative. This course introduces techniques for recommender systems and its application in a wide range of business settings such as movie recommendation, click-through-rate prediction, online dating, buyer-seller and producer-distributor matching, fashion outfit composition, and product sales forecasting. We first introduce the notion of personalization and latent representation. Then we discuss canonical recommender systems, c.

MKTG 6052: Marketing Analytics: Managerial Decisions

Modern marketers use data to drive decisions. This course teaches students a suite of statistics analytic tools to make strategic decisions. Focusing on learning how to apply specific analytic tools to different managerial challenges, students will learn how to leverage data to perform market analyses, segmentation and targeting, customer value assessment, brand management, new product development, among other tasks. Students will be able to apply the learned skills to their work immediately to produce data-driven insights and develop strategic recommendations. The course is also helpful for students who are interested in STEM to improve their stats modeling and other relevant skills.

MILI 6963: Healthcare Analytics

This course prepares students to analyze large health care databases with a focus on advanced applications with health insurance claims data. The course is designed to be a STEM offering with the use of statistical programming languages including R, Tableau, and SAS. This course is designed to appeal to students with an interest in developing data science as a core skill and already have knowledge of some programming tools, and experience with data manipulation in Excel, SQL, or Access. The course utilizes a novel synthetic health insurance claims database representing 300 million covered lives of the major private and publicly insured insured populations in the United States. Major topics include market sizing, actuarial projection, quality of care metrics, and national health account calculation.

FINA6322 - Financial Modeling

Financial modeling tools to access financial data warehouses to build, estimate, maintain, and interpret comprehensive financial models that provide the framework for understanding businesses and their historical performance, plans/strategies, and market values. Financial analytics/modeling skills, including data mining of large standard financial databases (warehouses) (e.g. Capital IQ), and a manageable introduction to Excel VBA programming.

SCO6085: Sales, Inventory, and Operations Planning

Sales, Inventory, and Operations Planning (SI&OP) is an important business process for any firm and can provide significant payoffs through achieving a balance between supply and demand. Using analytical tools and field data, SI&OP links a company’s strategic goals at the high level with its production at the tactical level while coordinating different business elements including manufacturing, finance, operations, sales, marketing, HR, etc. The output of an SI&OP process serves as guidance for various production functions such as the master production schedule (MPS) as well as material requirements planning. SI&OP focuses on getting the big picture right via balancing demand and supply at the product family level.

This 2-credit course is designed (1) to provide an overview of the entire SI&OP process, (2) to introduce the crucial inputs (i.e., forecasting and inventory management) to SI&OP, (3) to explain how the output of SI&OP (i.e., aggregate plan) is used as a guidance for planning production and material procurement, and (4) to expose students to several analytical tools used for the SI&OP process. To achieve these goals, the course covers a range of topics including forecasting, inventory management, aggregate planning, master production scheduling, and material requirements planning.