Why Penn State
We know there’s a lot to consider when deciding to earn a graduate degree in data analytics. Why should you choose Penn State Great Valley?
- Choose a program which meets your career goals – you may choose to focus on practical application with the Master of Professional Studies in Data Analytic or research with the Master of Science in Data Analytics.
- Work with local companies and faculty on research projects through the Big Data Lab, Do iT Lab, and Smart Systems Research Group.
- Attend at your own pace, completing on a part- or full-time basis.
- Become a part of the more than 750,000 Penn State alumni across the world.
- Courses taught by world-class faculty and industry experts.
- Both programs are STEM designated.
- Partner with alumni and local employers on relevant projects while fostering industry connections, networking, and job opportunities.
- Navigate problems that span a variety of industries.
- Immerse yourself in small classes and develop meaningful relationships with faculty and classmates who are business professionals and managers in the private and public sectors.
- Take advantage of Career Management Services, which offers a variety of programs, resources, and networking opportunities for students and graduates.
- Benefit from a STEM designated program, allowing 36 months total of Optional Practical Training (OPT).
In U.S. News & World Report’s 2023 "Best Online Programs," Penn State Great Valley is ranked:
- #3 in master’s in engineering programs
- #10 (tie) in master’s in computer information technology programs
In U.S. News & World Report’s 2023 "Best Online Programs for Veterans," Penn State Great Valley is ranked:
- #1 in master’s in engineering
- Courses are offered either in an in-person/online hybrid format or fully online.
- Fully in-person courses are available each semester to comply with visa requirements.
- Ability to simultaneously pursue another degree as part of the concurrent degree program.
Master of Professional Studies
Master of Science
|Capstone project completed in one semester||Thesis completed over at least two semesters, ending with public defense|
|Preparation for data-driven careers||Preparation for research and Ph.D. programs|
|Full-time completion in as little as one and a half years||Full-time completion in as little as two years|
|Part-time completion in three to four years||Part-time completion in three to four years|
|Students typically already have work experience||Students typically are fresh out of undergraduate studies|
|GRE scores not required for admission||GRE scores required for admission|
- Consists of six required courses, three electives, and one capstone course.
- Capstone course builds upon the theories, technology, and skills learned in previous coursework.
- Recent projects including creating an analytical pipeline to predict Alzheimer's Disease, detecting mask compliance in real-time, analyzing character networks and relationships in literature, predicting high-risk borrowers, identifying and deleting duplicate questions on websites with user-generated content, and more.
- Consists of five required courses, three electives, and a thesis paper.
- Thesis paper is six credits taken over two terms and requires the completion of CITI training.
- Recent papers have focused on information extraction and simplification from complicated medical notes, analyzing economic resilience, RNA sequencing, disease prediction, modeling resilience of economic infrastructures, predicting Autism Spectrum Disorder based on genetic profiles, economic loss caused by disruption in infrastructure networks, reinforcement learning, and more.