Q: What is the difference between the Master of Professional Studies and the Master of Science in Data Analytics?
A: The Master of Professional Studies (MPS) in Data Analytics teaches students to design, implement, and apply data analysis techniques to a broad array of industries that use and analyze high quantities of data to determine trends, construct models, and make strategic decisions. This degree has a practice-oriented capstone and is ideal for those who want to immediately apply what they have learned.
Through its emphasis on research, the Master of Science (MS) in Data Analytics is designed to prepare students for entry into data analytics doctoral programs. Rather than a capstone course, this program requires six credits of supervised research, culminating in a thesis paper. This program is ideal for those who want to enter a doctoral program, conduct research, or teach.
Q: How many credits are required?
A: Both the MPS curriculum and MS curriculum are composed of 30 credits. Schedule a meeting with a program representative for more information.
Q: Are the programs STEM designated?
A: Based in the tech-savvy Greater Philadelphia region, our programs cultivate the skills to collect, classify, analyze, and model data. Both programs are STEM designated, allowing 36 months total of Optional Practical Training (OPT), compared to 12 months for non-STEM degrees.
Q: Does it matter if I don’t have an engineering or technology undergraduate degree?
A: Data analytics students usually have undergraduate backgrounds in quantitative fields such as IT, engineering, business, or math, with at least one semester of college-level statistics or probabilities. While there is no work experience requirement for admission, students are often employed in industries such as business, computer science, finance, healthcare, or pharmaceuticals. If you come from a different background, we may ask that you complete the pre-requisite course IST 140.
Q: Does the program offer any experiential learning opportunities?
A: Yes, our instruction and facilitation lean heavily on active and experiential learning techniques. Problems assigned in our courses use real-world datasets from companies and organizations, social media scraping, or government agencies (like NIH, DoT, Veterans Affairs, etc.). Students must address real business, social, or technical problems with these datasets using industry-standard toolsets, evaluate both their approach and outcomes, and reflect on the efficacy of their methodologies and solutions.
Q: Do you allow students to transfer credits into the program?
A: A maximum of 10 graduate credits earned at another accredited institution may be applied. Courses must have been completed, with a grade of B or better, within five years prior to the date of enrollment. Up to 15 credits from Penn State nondegree and graduate certificate courses can be applied to a degree program—more information can be found here. Transfer credit approval is granted by the student's academic adviser and division head after an admission offer has been accepted.
Q: I am worried about flexibility. How are classes delivered?
A: Flexible, seven-week courses let you balance your busy schedule while still reaping the benefits of once-per-week face-to-face classes, like networking and developing interpersonal skills.
Q: I've been out of school for 15 years. Will I feel out of place taking classes after all that time?
A: The average age of our students is 32. You will find most of our students share the same concern and worry how they will be able to juggle graduate school with an already busy life. Our data analytics programs are designed for the needs of working adults.
We encourage those who are not sure about committing to a master’s degree to consider beginning with a graduate certificate—which, in most cases, allows for credits earned to transfer to the degree program upon admission. Each semester, prospective students can take advantage of our “test drive” program, which offers the opportunity to sit in on a class. To arrange a test drive, email [email protected] and a program representative will reach out to discuss options with you.
Q: How long will it take me to graduate?
A: The choice is yours! We provide flexibility for students, many of whom may be using tuition benefits from their employer or financing their studies on their own. Students can take up to eight years to complete a degree program, and up to three years to complete a graduate certificate. The average completion of a degree program is between two and a half to three years when pursued on a part-time basis, and up to two years if pursued full time.
Q: Are career services provided?
A: Yes. We have a Career Management Services office that provides one-on-one career advancement support, internship guidance, access to career fairs and other career events with local and national companies, as well as an array of other services. An additional perk of being part of the Penn State family is free career services for life!
Q: Is there an application fee? What are the application deadlines?
A: Yes, there is a $65 application fee. Schedule a meeting with a program representative to discuss eligibility for an application fee waiver. We recommend applying no later than July 15 for a fall (end of August) program start, or December 6 for a spring (January) start. See the admission requirements page for more information. International application deadlines may differ; for more information visit the international applicant page.
Q: Is the GMAT or GRE ever waived?
A: GRE/GMAT scores are not required for the MPS program. The MS program requires applicants to submit official GMAT/GRE results.
Q: Where can I find information on scholarships and funding options?
A: There are a variety of scholarships available to half-time and full-time students who meet certain criteria. More information can be found here.
Q: Are there program metrics?
A: The Graduate School provides metrics on admission data, GMAT/GRE scores, enrollment, student demographics, time to degree, and degree conferral; more information can be found here.