Join our results-focused MS program and develop the credentials employers want in one of the world's top markets for tech talent.
Our program trains students of diverse backgrounds — computer science majors and those pivoting into the field — through a common core curriculum and specializations in applied computer science, cybersecurity, game and computational media, or data science. Students may receive funding as research assistants working with professors or in other university roles.
Request Info How to Apply
- Mode of Study
- Time to Complete
18 mos. or your own pace
- Course Scheduling
Variable, mostly afternoons and evenings
30 credits with
- Tuition and Funding
$1922 per credit. All applicants automatically considered for merit scholarships; visit Tuition and Funding.
Start in fall or spring; no GRE scores or tech degree required: Admission and Requirements.
Current Research areas include computational science and signal processing; cybersecurity, data science, AI, and machine learning; neuroscience, visual/tactile perception, and DNA sequencing; game design, illusions, and social simulations.
DC Career Launch
The DC tech sector of federal and state agencies, NGOs, higher ed, and contractors/consultancies offers max career choice — with triple the national concentration of computer science jobs and starting salaries for MS graduates over $100K.
Specialize Your Studies
The MS program offers students 4 specializations:
- Applied Computer Science
- Data Science
- Game and Computational Media
Students choose their specialization while completing a 5-course common core. Starting in their penultimate semester, they begin work on an expansive capstone project with theoretical or practical options: Internship and Project, Project, or Thesis.
Beyond the capstone, students may work with faculty projects and labs, including the AU Game Center and Game Studio (for persuasive play and interactive media); Design and Build Lab (prototyping and digital fabrication); Data Science Lab (machine learning development and application); Lab for the Study of Sensation, Perception, Reality, and Illusion; and Computational Material Perception Laboratory (applying human perception principles to improve machine perception). Our students intern with a range of local, national, and international firms, often on campus or arranged through AU alum networks.
Recent student projects and internships include
- Prediction of Breast Cancer Recurrence with Machine Learning
- Music as a Memory Enhancer: A Music Therapy Web Application for Dementia Patients
- Pocket Legal: Exploring Open-Access API Content & Features to Create a Legal Literacy Dashboard
- Adopt A Pixel Project: Developing Useful Products to Boost Effective Learning for NASA GLOBE (Global Learning and Observations to Benefit the Environment)
- DealRoom: Machine Learning Intern building machine-learning prototype on AWS Sagemaker for a model that will analyze and rationalize trends in the M&A landscape for the recent 100 years.
- Workday: Technology Analyst assisting with enterprise-level implementation of finance, budget, and HR software applications.
- Reep Technologies: Machine Learning Intern testing machine learning results quality and developing protocols.
Students progress through three phases of the program for the required 30 credits:
- 5 core courses: 621 Design/Organization of Programming Languages; 634 Database Management Systems; 650 Software Engineering; 665 Operating Systems; and 668 Artificial Intelligence.
- 6-credit Capstone with three options: Internship and Project, Project, or Thesis
- 9 elective credits in their chosen specialization:
- CSC-676 Computer Vision (3)
- CSC-680 Introduction to Data Mining (3)
- CSC-685 Introduction to Information Visualization (3)
- CSC-696 Selected Topics: Non-Recurring (1-6)
- DATA-613 Data Science (3)
- DATA-641 Applied Natural Language Processing (3)
- DATA-642 Advanced Machine Learning (3)
- ITEC-620 Business Insights through Analytics (3)
- ITEC-621 Predictive Analytics (3)
- STAT-627 Statistical Machine Learning (3)
Game and Computational Media
Visit our Admission and Course Requirements page for complete curricular and admission details, and guidance for international students.
“The community at AU is tight knit. It’s easy to contact professors, conduct independent studies, and participate in faculty research. Professors within the program explore many different areas of studies, so it is easy to learn from them and obtain internship and career opportunities through their advice and recommendations. ”
—Yanet Yilma, MS Computer Science alumna ’23
The Bureau of Labor Statistics reports a median annual salary over $131,000 for Computer Scientists with starting salaries for MS graduates exceeding $100,000 nationwide as of 2021 (typically a 30-50% higher than starting salaries with bachelor's degrees). The DC metro area has triple the national concentration of jobs and job growth projected above the 21% national rate over the next decade.
In DC and surrounding areas, you'll be able to take advantage of the concentration of federal and state agencies, private contractors and consultancies, business, NGOs — and AU's active alumni network — to find career choices you want. Recent graduates have gone on to a range of positions at firms including
- Adobe Systems Incorporated
- Amazon Web Services, Inc.
- Applied Research in Acoustics LLC
- Association for Women in Science
- CyberData Technologies, Inc.
- Guidehouse Defense & Security
- Lockheed Martin
- Pew Research Center
- US Air Force
- United Technologies
- Walmart Labs
- Williams-Sonoma, Inc.
What You'll Walk Away With
- Software development skills: design, develop, and implement software systems, including requirements analysis, design, implementation, testing, database management, and deployment.
- Communication and teamwork skills: practical experience with technical documentation, including testing, security, and maintenance planning; competence with position or research papers and case studies; ability to collaborate with both technical and non-technical colleagues.
- Cybersecurity: ability to stay up to date on evolving risk management, cyber-attack, and digital forensic trends and techniques; advanced understanding of network security protocols, technologies, tools, and best practices; demonstrable expertise with computer vision, crypto algorithms, and legal or ethical standards.
- Data Science: create ethical, data-driven solutions for real problems in diverse fields; collect, clean, and organize large amounts of data from open data sites, through APIs, via web scraping or from SQL-based databases; develop reproducible analyses
Ready to dive in?