Data Science Curriculum Design: A Case Study

There is an increasing demand for data scientists in the current job market. Hence, many two-year and four-year colleges and universities started to offer Data Science degrees in the recent decade. In this paper, we describe an undergraduate Data Science curriculum that focuses on computational skills and mathematical foundations, with inclusion of a domain in business analytics. We expect this paper to be used by institutions as a guideline while planning their Data Science undergraduate degree. We reviewed around 100 undergraduate Data Science programs in the U.S. and summarized their common approaches and we also reviewed several Data Science curriculum development guidelines. Then, we developed our interdisciplinary undergraduate Data Science program that consists of (1) mathematics and statistics foundation courses covering discrete mathematics, linear algebra, introductory statistics, analysis of variance, and regression, (2) computer science foundation courses covering two programming languages (namely Python and Java), data structures, and database management, (3) core data science courses covering data science and visualization, statistical machine learning, data mining, and machine learning, and finally (4) courses from the business domain covering business intelligence analytics and predictive analytics. At the end of the degree program, we include a choice among a senior capstone course, a statistical consulting course, or an internship. We also discuss the collaboration between departments and colleges for this program.