Students will learn the fundamentals of product management. Topics include identifying unmet needs, understanding markets, implementing product development frameworks and processes, building businesses, and working with multi-functional teams. The application of these concepts to different phases of the product lifecycle will be explored. Students will build technical, professional, and soft skills necessary for success in product management. Prerequisite: EBUS 1800 and enrolled in the Engineering Business Minor or Entrepreneurship Minor - Tech Concentration and 3rd or 4th year standing

The course is designed to not only teach students tools necessary to visualize data but also effective techniques for explaining data driven results with an emphasis on communicating statistical output in a manner that best represents the findings. Examples might include tailoring messages based on the audience or shaping visualizations to follow a story-line. Content on the development of interactive plots and dashboards will also be included.

This interdisciplinary course introduces students to critical global economic and cultural issues and examines globalization at a variety of scales of analysis (planetary, regional, national, individual). The goal is to provide understanding of the main conceptual approaches to global studies and thus enhance their ability to understand and evaluate important real-world issues and problems.

Covers the fundamentals of probability theory & stochastic processes. Become conversant in the tools of probability. Clearly describe & implement concepts related to random variables, properties of probability, distributions, expectations, moments, transformations, model fit, basic inference, sampling distributions, discrete & continuous time Markov chains, & Brownian motion. Illustrate most topics with both analytic & computational solutions.

Explores principles and applications of data ethics within a broader social framework that prioritizes conversations about policy, regulatory frameworks, accountability, transparency, and governance models. Will discuss who is responsible for doing responsible data science, question how our work shapes the world around us, and understand the impacts of big data on people and communities.

This course will center on exposing students to contemporary pipelines for data analysis through a series of steadily escalating use cases. The course will begin with simple local database construction such as SQLite and evolve to cloud base systems such as AWS or Google Cloud. This progression will include topics such as data lakes and other non-SQL applications as appropriate.

This class is an introduction to Latin dancing including Salsa, Bachata, Merengue, Cha-cha and other forms of Latin partner dance. We will cover the fundamentals of leading and following, as well as beginner and intermediate dance patterns, musicality, and styling for each dance.

An overview of the fields of social psychology and behavioral science. We will explore behavioral research in basic social psychology, leadership and organizational behavior, and the ways in which social science methods and research are currently being used in public policy and to solve major societal problems. The ultimate goal is to teach students how to think like behavioral scientists.

'Impact Investing' is the proactive deployment of financial resources to organizations for a positive return on investment and an additional, intentional social impact beyond financial returns. Impact Investing explores how funders (grant funders, investors, and policymakers) deploy capital to support social entrepreneurs. This course provides an introductory understanding of utilizing finance as a tool for solving social problems worldwide.

Trends in hardware and software for Big Data Systems and applications. Cover principles driving data infrastructures, which enabled the training of AI models on datasets (speech, sounds, images, video, languages) and may extend to structured data (text, images, time series). AI and machine learning practitioners build and deploy data science projects on Amazon Web Services unifying data science, data engineering, and application development.