The focus is private equity in the context of financing innovation especially from the investor?s perspective. This course covers screening entrepreneurial ideas and business plans through the spectrum of entrepreneurial financing stages from seed, start-up, later-stage financing, to acquisition/buyouts and IPOs. Students will research, discuss and present state-of-the-art analyses and practices and have exclusive access to PitchBook database that provides users intelligence on the private markets, angels, venture capital, mergers & acquisitions, and private companies.

This course immerses students in the intersecting realms of technology and business. Students will explore key domains such as Artificial Intelligence, Cybersecurity, Global e-Business, Application Design, and Enterprise Systems, engaging in a hands-on, collaborative curriculum. Students will develop a strategic perspective on using IT innovations to drive business value, tackle real-world challenges, and build in-demand skills for dynamic technology careers.

The course is designed to provide an introductory understanding of the fundamentals of uncertainty quantification in business decision making. The course will serve as a building block for subsequent course work in inferential statistics, predictive analytics, and time series analysis. The topics include the axioms of probability theory, random variables, probability distributions, random variable generation using simulation methods, and system simulation for relevant business applications (e.g. inventory management, supply chain management, and staffing in call centers). An introduction to the programming language R will be part of the learning experience.

The goal of this course is to expose students to techniques and technologies that will enable them to collect, harvest and transform unstructured and structured data into useful business insights. The first half of the course deals with data management and provides an introduction to data types and sources, data acquisition and harvesting tools and techniques and effective strategies and methods for data aggregation and analysis. In the second half of the course, students learn about the theoretical underpinnings of data visualization and use a variety of software tools to visualize business data in order to generate insightful information that facilitates effective business decision making.