Students will use analytics to study a wide variety of issues affecting the sport industry. Topics examined include: player performance measurement, in-game decision making, player selection/team building, and general administration such as marketing, pricing, contracts, stadium management, etc. Students will learn not only how the recent application of analytics has improved each of these areas within the professional and collegiate sport industry, but also how analytics can improve decision making in any other field of business.

Introduction to mathematical methods for solving problems in physics, including approximation methods, complex algebra, ordinary differential equations, the harmonic oscillator, and linear algebra including matrix diagonalization and eigenvalue problems.

Provides an introduction to project management, focusing on the integration of business operations and information management, and techniques to effectively manage the implementation of such projects.

The Artificial Intelligence in Business is designed for business major students aspiring to develop a deeper understanding of artificial intelligence and its use in business applications. The course will provide an introductory overview of different mathematical and computational data analysis tools and machine learning techniques commonly used in artificial intelligence. Focus will be on case studies and applications that demonstrate how artificial intelligence can augment current business operations.

The Artificial Intelligence in Business is designed for business major students aspiring to develop a deeper understanding of artificial intelligence and its use in business applications. The course will provide an introductory overview of different mathematical and computational data analysis tools and machine learning techniques commonly used in artificial intelligence. Focus will be on case studies and applications that demonstrate how artificial intelligence can augment current business operations.

In the digital age, the ability to analyze and interpret marketing data has become essential for success. This course, Applications of R for Marketing and Analytics, is designed to equip students with the skills needed to harness the power of data in making strategic marketing decisions. Through a blend of theoretical concepts and hands-on practice, students will learn how to clean, analyze, and visualize marketing data from real world datasets.

Marketers use a broad array of evolving tools, from Direct Mail to Social Media. In this course, students learn about the range of these tools, related data sources, and online and offline metrics for evaluating their success. The course stresses combining different marketing resources (for example, bricks and mortar stores with online channels; online landing pages to test offline media with google analytics).

This course will introduce concepts of engineered tissue replacements and tissue model systems for basic research. We will discuss the growing need for tissue replacements, in vivo cell-matrix relationships in biology, and how we can engineer biomaterials (both bioinert and bioinstructive) to act as cell scaffolds.