GBUS 8496: Data Science in Business (3.0 Credit Hours)
Academic Course Description
New cases provide opportunities to learn how data science is affecting a variety of domains, from entrepreneurship and marketing to operations and finance. In this course, students will gain exposure to the concepts and tools used by managers to create disruptive business models that leverage big data. The concepts and tools covered include algorithm design, feature selection, data visualization, web scraping, cloud computing, database querying, and text analysis. Through materials designed for the novice, students will learn to code in R (a popular statistical computing language) and develop cutting-edge prediction algorithms from large datasets, sometimes on a virtual machine in the cloud. Teams will often compete to develop accurate forecasts. Winners will be determined by performance on holdout samples of real data. Students will also learn good data visualization, a big part of both generating accurate forecasts and presenting them to others. The forecasting topics covered include time series forecasting, advanced regression, machine learning, and text analysis.
Academic Course Objectives
· Examine the tools and concepts used by data scientists.
· Learn to code in R and design good forecasting models and machine-learning algorithms.
· Develop good data visualizations.
Elements of the Course Grade
Class contribution 40%
Individual paper/project 20%
Group paper/project 40%