In today’s information society, professionals who can make sense of big data are in high demand. The Data Sciences (DS) degree program at Penn State is part of an intercollege initiative between the College of Information Sciences and Technology (IST), College of Engineering, and Eberly College of Science to meet that need. The curriculum for the DS major is designed to equip students with the knowledge and the skills needed to elicit, formulate, and solve data sciences problems using modern informatics, computer science, and statistics tools for data management, machine learning, information integration, and predictive modeling, and effectively communicate their findings to a broad range of stakeholders. The students will gain the critical analytical skills needed to assess the feasibility, benefits, limitations, risks, and ethical implications of applying data sciences methods in different settings. Through experiences such as the capstone project, students should be prepared to function effectively as members of interdisciplinary data science teams to harness the potential of data to enable discovery, optimize products and processes, and inform public policy.
How it Works
Data Sciences is an interdisciplinary field concerned with the integration of methods, processes, systems, and tools from Information Science, Computer Science, and Statistics, to discover, validate, and apply knowledge and actionable insights from data, across a broad range of application domains. Students in Penn State’s DS major will specialize in one of three options: Applied, Computational, or Statistical Modeling data science. Students will gain breadth of knowledge through common core classes, as well as depth in one of the three options. After taking common courses during the pre-major stage, students will choose among the Applied option (offered by IST), the Computational option (offered by Engineering), and the Statistical Modeling option (offered by Science). Students in all three options will come together in their junior and senior years for two shared capstone experiences.
Students in the Applied Data Sciences option will receive additional cross-training in an application domain so they are able to effectively formulate and solve data science problems in the context of the chosen domain, such as life and health sciences, business, cognitive sciences, organizational and social sciences, physical sciences, agricultural sciences, among others. Learn more
Computational Data Sciences
Students in the Computational Data Sciences option will receive additional training in Computer Science to be able to design, analyze, implement, and deploy advanced algorithms, hardware and software architectures, and systems for data management and analyses.Learn more
Statistical Modeling Data Sciences
Students in the Statistical modeling Data Sciences option will receive additional training in Statistics to be able to formulate, develop, and apply the proper statistical models and methods for data analyses, e.g., experiment design, sampling, hypotheses testing, and limiting false discovery.Learn more