Discover B.S. in Data Sciences

Unlocking Big Data

Penn State offers a unique Data Sciences bachelor's degree program that pulls in strengths from three colleges to help you learn the technical fundamentals of data sciences and the skills to manage and analyze large-scale unstructured data. You’ll take two years of common courses and then select from one of the three options below to explore in depth. These options include:

  • Applied Data Sciences option (offered by the College of Information Sciences and Technology)
  • Computational Data Sciences option (offered by the College of Engineering)
  • Statistical Modeling Data Sciences option (offered by the Eberly College of Sciences)

“Every company needs people who speak the language of data. It’s exciting to be on the forefront of this growing field, and the College of IST does a great job of preparing you to be a data scientist in the real world.”

Sean Parsons, Class of 2020

Finding Your Fit

Data Sciences might be the right program for you if:

  • you are curious about analyzing information to discover new insights
  • you want to apply data analytics to make strategic decisions
  • you want to understand how data can be used to visualize phenomena and predict different outcomes
  • you are interested in statistics, mathematics, and the social sciences, and want to combine these disciplines to understand what data is really telling us

Developing Your Skills

In the Data Sciences program, you will take hands-on courses to help you learn how to develop, apply, and validate machine learning solutions to extract actionable knowledge from large data sets. Teamwork, project management, and collaboration play vital roles in your IST experience. You will have opportunities to apply your newfound knowledge and skills through semester-long projects with your peers.

Sample Courses

Review the Suggested Academic Plan to see the courses you could take, including:

  • DS 200 – Introduction to Data Sciences
  • IST 230 – Language, Logic, and Discrete Mathematics
  • DS 310 – Machine Learning for Data Analytics
  • DS 320 – Data Integration
  • DS 330 – Visual Analytics for Data Sciences
  • DS 410 – Data Analytics at Scale

Application Focus Areas

Within the Data Sciences program, you’ll learn to apply data sciences concepts to a specific domain by choosing one of the application focus areas below or working with faculty and advisers to create your own:

  • Astronomy
  • Food Science
  • Health Sciences
  • Information and Cybersecurity Sciences
  • Life Sciences

Discovering Your Path

At the College of IST, every undergraduate student is required to complete at least one internship before graduating. With more than 300 organizations actively recruiting students and a dedicated Career Solutions team, you’ll have the resources and opportunities to get your career off to a strong start.

Potential Careers

Past Student Internships

Examples of the work done in past data sciences internships held by our students include:

  • developing machine learning software for signal analysis
  • analyzing data from a web-based conversational bot
  • leveraging predictive analysis tools and databases to enhance projects
  • building, validating, and deploying predictive models using machine learning technologies
  • developing code for data mining, statistical analysis and prediction systems that align with a company’s strategic goals
  • analyzing corporate data to identify market trends

Recent Graduate Positions

Examples of positions our graduates have recently accepted include:

  • Big Data Engineer
  • Business Intelligence Analyst
  • Data Scientist
  • Data Visualizer
  • Data Warehousing Analytics Consultant
  • Quantitative Analysts
  • Statistical Analyst
  • Systems Analyst

"With the explosion of big data, we are attempting to untangle, understand, and harness the power of the massive amount of information now available to us. Data Sciences provides us the framework to do this."

Yuya Ong, Class of 2019
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Office of Undergraduate Recruiting

E103 Westgate Building
University Park, PA 16802