Learn to collect, classify, analyze, and model data across domains using statistics, computer science, machine learning, and software engineering with Penn State Great Valley's graduate Data Analytics programs.
We offer two distinct options: the Master of Data Analytics (MDA) focuses on practical application; the Master of Science (MS) in Data Analytics is a research-focused program.
With our graduate Data Analytics programs, you can:
- Work with local companies and faculty on research projects through the Insights 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.
- Learn from world-class faculty and industry experts.
- Both data analytics programs are STEM designated.
- GRE not required for the MDA program, but is required for the MS in Data Analytics.
Program Advantages
- 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).
- Ability to simultaneously pursue another degree as part of the concurrent degree program.
Flexibility & Delivery
The Master of Data Analytics (MDA) features two delivery options: hybrid delivery or fully online. The Master of Science in Data Analytics is available in hybrid delivery format.
Hybrid
Hybrid delivery combines flexibility with the advantages of in-person instruction on our state-of-the-art campus. Courses are delivered in convenient, seven-week sessions via an in-person/online hybrid format. Many of these courses meet once a week in person and once a week online. Some courses may be delivered fully online.
Hybrid courses meet requirements for international students studying on an F-1 or J-1 visa.
Fully Online
To learn about our fully online Master of Data Analytics, visit the Master of Data Analytics via World Campus.
Stackable Credentials
Demonstrate your new skills prior to earning your master’s degree through our stackable Graduate Certificates. You can earn the following certificates within the curriculum of the Master of Data Analytics/Master of Science in Data Analytics degree:
Data Analytics Certificate
A 9-credit certificate covering how to present data in visual and meaningful ways, create analytics solutions for business problems, and use quantitative methods to support business decisions.
Data Engineering for Analytics Certificate
A 9-credit certificate focused on programming skills, data management, and software lifecycle methodologies.
Foundations of Data Science Certificate
A 9-credit certificate covering machine learning, deep learning, statistical analysis and computing, and processing large amounts of data.
Curriculum
Below is a breakdown of differences between the two degree options in Data Analytics:
Master of Data Analytics |
Master of Science in Data Analytics |
| 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 |
Master of Data Analytics
- 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.
Master of Science in Data Analytics
- 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.
Penn State Great Valley Rankings
In U.S. News & World Report’s 2024 "Best Online Programs," Penn State Great Valley is ranked:
- #3 in Master’s in Engineering programs
- #5 in Master's in Engineering Management (specialty ranking)
- #7 in Master’s in Computer Information Technology programs
In U.S. News & World Report’s 2024 "Best Online Programs for Veterans," Penn State Great Valley is ranked:
- #2 in Master’s in Engineering programs
- #4 in Master’s in Computer Information Technology programs
