Effective Fall 2019

Modifications Made to Curriculum: Fall 2025

An applied program that teaches students how to draw information from data. The curriculum involves courses in statistics, data science, and programming, as well as applied data analytics projects and internship opportunities across many different disciplines and industries. Students complete the program with a portfolio of data analytics projects highlighting the application of their skills to internship and case study projects. 

Advanced Research

Data Science students focus on the intersection of statistics and computer science, with content knowledge from another discipline or industry and an emphasis on applying skills and technologies in case studies courses, internships, and capstones aligned with a student’s interests. Experiential learning is a critical component of this curriculum, in line with Drew University’s mission across all three schools.

Curricular Components

Courses emphasizing Big Data explore how to obtain, prepare, and manage data from a wide variety of sources. Students work with big data scraped from the web and from social media.

Courses emphasizing Data Analysis explore how to master various data analytical techniques. Students apply data analytics to numerous disciplines, through data analysis, visualization, computer simulation, and computer modeling. Students learn the uses, potential, and limitations of the tools of computing technology as a foundation for research and knowledge acquisition in disciplines and in society.

Courses emphasizing Communication of data-driven conclusions explore the results based on an analysis of real-world data. Students work collaboratively. Applied data science is multidisciplinary involving the interplay between statistics, computer science, and different disciplines. The focus of all classwork is on practical applications and the communication of results. Students leave the program with a portfolio of project work and with work experience from their internships.