The Penn State Great Valley Master of Software Engineering will provide you with the technical IT skills needed for various IT and web-based careers, from applications developer to web designer.
With our Master of Software Engineering program, you can:
- Prepare to create large-scale software products and services for industry and government through software analysis, architecture, design, development, and testing.
- Work on industry-sponsored projects or research with faculty through the Insights Lab.
- Pursue your degree at your own pace, completing in as little as two to three years if attending part-time, or 12-18 months if attending full-time.
- Engage in courses taught by world-class faculty and industry experts.
- Experience a collaborative and innovative experience rooted in practice—providing you with the skills, experience, and perspective to become a leader.
- Become a part of the more than 750,000 Penn State alumni across the world.
GRE is not required.
Program Advantages
- Partner with alumni and local employers on relevant projects while fostering industry connections, networking, and job opportunities.
- 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.
- Prepare for future leadership roles.
- Take advantage of Career Management Services, which offers a variety of programs, resources, and networking opportunities for students and graduates.
- Explore different areas of interest through a wide range of electives.
- Engage in hands-on courses through weekly assignments and team-based, term-long projects.
- Benefit from a STEM designated program, allowing 36 months total of Optional Practical Training (OPT).
Flexibility & Delivery
The Master of Software Engineering features two delivery options: hybrid delivery or fully online.
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 delivery option, visit the Master of Software Engineering via World Campus.
Curriculum
The 36-credit program focuses on requirements engineering, software systems architecture, software systems design, software testing, software construction, mobile and cloud computing, technical project management, and more.
This cutting-edge curriculum includes new courses in mobile and cloud computing, artificial intelligence, machine learning, and big data.
The capstone project immerses you in the complete software development lifecycle, engineering a fully functional product following an iterative incremental developmental methodology with change management, continuous integration, continuous delivery, and automated testing.
Stackable Credentials
Demonstrate your new skills prior to earning your master’s degree through our stackable Graduate Certificates. You can earn up to three related certificates within the curriculum of the Master of Software Engineering degree:
Project Quality Management Graduate Certificate
A 12-credit certificate covering how to design and implement test strategies to ensure software quality, and plan, organize and execute a project from start to finish.
Software Architecture and Design Graduate Certificate
A 9-credit certificate covering analyzing, designing, implementing and managing the technical development aspects of a software system.
AI Engineering Graduate Certificate or Data Analytics and Engineering Graduate Certificate
The 12-credit AI Engineering certificate covers programming, machine learning, deep learning, and natural language processing. The 12-credit Data Analytics and Engineering certificate focuses on preparing students to design, build, and maintain infrastructure for managing and analyzing large volumes of data.