University of Missouri-Kansas City

What you'll study

The applied MS in Computer Science emphasises advanced, hands-on study across core areas of computing while allowing specialisation in topics aligned with industry needs. Typical core and elective topics include:

• Algorithms and Data Structures – advanced algorithm design, analysis and optimisation techniques.
• Software Engineering – software architecture, testing, agile development and DevOps practices.
• Databases and Information Management – database design, distributed data systems and data modelling.
• Computer Systems and Networking – operating systems, distributed systems and cloud computing fundamentals.
• Machine Learning and Data Science – supervised and unsupervised learning, model evaluation and applied data analytics.
• Cybersecurity and Privacy – secure software development, network security and applied cryptography topics.
• Electives and Special Topics – courses in mobile and web development, human–computer interaction, computer vision, big data and other contemporary areas.
• Capstone or Thesis – students typically complete a project-based capstone or a research thesis, working individually or in teams with faculty supervision or industry partners to apply learned skills to a real problem.

The programme is delivered through a mixture of lectures, lab work and project-based assignments. Students may follow a coursework-only route emphasising applied projects, or select a research-oriented thesis route if they plan to continue to doctoral study or research roles.

Entry requirements

Applicants are normally expected to hold a recognised bachelor’s degree in computer science, computer engineering, or a closely related discipline. Where a degree is in a different field, successful applicants should demonstrate substantial undergraduate coursework or professional experience in programming, data structures and discrete mathematics.

• Transcripts from all post-secondary institutions demonstrating satisfactory academic performance.
• A statement of purpose outlining academic and professional objectives and how the applied MS will support those goals.
• Letters of recommendation, typically one to three, from academic or professional referees.
• Evidence of preparation in core computing topics; applicants missing prerequisites may be asked to complete specified bridge courses prior to full admission.
• International applicants must satisfy English language proficiency requirements through recognised tests or equivalent qualifications.

Standardised tests (such as the GRE) may be considered where submitted but are not universally required; applicants should consult the department for current testing policies. Part-time study and flexible scheduling options are commonly available for working professionals.

Career prospects

Graduates from an applied MS in Computer Science go on to roles across industry and government where practical technical expertise is valued. Common career paths include:

• Software engineer or developer, building web, mobile and enterprise applications.
• Data scientist or data engineer, developing models and pipelines for analytics and machine learning.
• Systems engineer and cloud architect, designing scalable distributed systems and cloud-native solutions.
• Cybersecurity analyst or engineer, securing applications and networks and managing risk.
• Technical lead, product engineer or engineering manager roles combining technical and project leadership responsibilities.
• Further study leading to doctoral research or roles in research and development.

Because of UMKC’s location within the Kansas City metropolitan area, students commonly find internship and employment opportunities with local technology firms, healthcare organisations, financial services, and manufacturing companies that seek applied computing skills.

Why study at University of Missouri-Kansas City

UMKC provides an applied computing programme with close ties to regional industry, offering access to internship opportunities and project collaborations that help bridge classroom learning and workplace practice. The department emphasises small-class interactions with faculty, hands-on labs and faculty supervision for capstone projects.

• Strategic metropolitan location with a growing technology sector and strong employer connections for internships and applied projects.
• Flexible delivery formats that accommodate full-time students and working professionals, including evening and hybrid course options.
• Faculty with applied research and industry experience across core computing areas, enabling supervision of practical capstone projects and applied research.
• Support services for graduate students including career services, professional development workshops and networking events with local employers.

Prospective students should contact the department directly for guidance on course planning, available specialisations and the most current information about admission pathways and programme options.