Graduate Programs

The Master of Science in Computer Science provides advanced technical depth beyond the undergraduate level and prepares students for professional advancement or doctoral study. The program strengthens expertise in algorithms, systems and software engineering while developing the ability to evaluate research, design computing solutions, and address complex technical challenges.

Students complete 30 credit hours, including core coursework in research methods and algorithm design, advanced electives at the 5000 and 6000 levels, and a culminating experience through either a thesis (Plan I) or project/internship (Plan II). At least 18 credits must be at the 6000 level or higher.

Graduates are prepared for advanced technical roles in industry and government or for continued study. Career paths include software engineer, systems architect, machine learning engineer, cybersecurity analyst, IT solutions engineer, data engineer and research scientist. These positions are in high demand across sectors such as technology, finance, healthcare, defense and consulting.

The fully online Master of Science in Software Engineering is designed for working professionals and career changers seeking to advance or transition into software development and technology-focused roles. The program provides a structured pathway into software engineering without requiring a prior degree in computer science or software engineering.

Students develop expertise in modern software engineering principles, including system architecture, secure development practices, database systems, quality assurance, DevOps practices and project management. The curriculum emphasizes practical application, enabling students to apply concepts directly within their professional environments.

The program consists of 30 credit hours of graduate coursework and includes an applied culminating experience such as capstone project courses.  

Graduates are prepared for roles such as software developer, DevOps engineer, systems analyst, quality assurance engineer, technical project manager and solutions architect. The program also supports professionals seeking advancement into senior technical or leadership positions within technology-driven organizations.

The Master of Science in Data Science is a multidisciplinary program combining computer science, statistics and applied analytics. Students develop expertise in programming, machine learning, statistical modeling and data mining, preparing them for advanced roles in data-driven organizations or for doctoral study.

The 30-credit program includes required coursework in data science principles, artificial intelligence and statistical methods, along with approved electives and a culminating project or internship. At least 18 credits must be at the 6000 level or higher.

Graduates are equipped to analyze complex datasets and communicate data-informed insights effectively. Career paths include data scientist, machine learning specialist, business intelligence analyst, data engineer, analytics consultant and quantitative analyst. These positions are among the fastest-growing in the job market, with opportunities in technology, healthcare, finance, retail and government analytics.

The Ph.D. in Data Science prepares scholars to advance the theory and practice of data science through rigorous coursework and original research. The program integrates advanced study in machine learning, big data analytics and statistical modeling with interdisciplinary coursework and applied data science experience.

Doctoral research fosters innovation in areas such as algorithmic fairness, scalable machine learning, causal inference, real-time analytics and distributed computing. The 60-credit curriculum includes core coursework, electives, an applied experience and a minimum of 16 credits of dissertation research. Students must complete a preliminary examination and defend their dissertation. 

Graduates are prepared for highly specialized research and leadership roles. Career paths include research scientist, postdoctoral scholar, advanced analytics director, chief data officer, academic faculty, principal data scientist and research lead in AI/ML labs. These careers are increasingly critical as organizations invest in next-generation data-driven innovation.