University of Colorado Boulder

What you'll study

The MS in Computer and Information Sciences combines core graduate-level computer science topics with options for research or coursework emphasis. Students follow a programme of advanced modules, seminars and a culminating research project or thesis depending on their chosen track.

• Core topics: advanced algorithms and data structures, operating systems and distributed systems, programming languages and software engineering principles, theoretical foundations of computation.
• Specialist areas: machine learning and artificial intelligence, data science and databases, computer vision, natural language processing, cybersecurity, human–computer interaction, information retrieval and computational biology.
• Typical modules: graduate algorithms, advanced machine learning, big data systems, database systems, cloud and distributed computing, security and privacy, human–computer interaction methods, research methods in computer science.
• Structure: programmes usually offer a thesis (research) option and a non-thesis (coursework/project) option. A thesis route emphasises original research supervised by faculty in areas such as AI, systems or HCI; the coursework route emphasises advanced classes and may include a capstone or practicum project with industry partners.
• Assessment: coursework, programming assignments, exams, project reports and, for thesis students, a formal thesis and defence or final presentation.

Entry requirements

Applicants are expected to hold a bachelor’s degree in computer science, information science, engineering, mathematics or a closely related discipline. Admissions typically require demonstrated competence in programming, data structures and discrete mathematics; strong applicants from other backgrounds should show evidence of equivalent coursework or practical experience.

• Academic transcripts: an accredited undergraduate degree with a solid academic record in relevant subjects.
• Prerequisites: prior coursework or experience in programming, algorithms, linear algebra and probability; some applicants may be required to complete preparatory courses if background is insufficient.
• Supporting materials: personal statement outlining research or career goals, letters of recommendation, and a CV. Applicants for research-focused tracks should identify potential faculty supervisors or research groups of interest.
• English language: proof of English proficiency if your prior study was not in English, in line with the university’s standard requirements.
• Standardised tests: check current department guidance on GRE or other test expectations; requirements can vary and may not be mandatory for all applicants.

Career prospects

Graduates of the programme move into a wide range of technical and research roles across industry, government and academia. The curriculum prepares students for positions that require advanced computing and information expertise.

• Industry roles: software engineer, machine learning engineer, data scientist, systems engineer, cloud engineer, site reliability engineer, security analyst.
• Information-focused roles: database administrator, information systems architect, search and recommendation engineer, HCI/UX researcher and developer.
• Research and academia: PhD admission in computer science or information science, research scientist roles in industrial research labs and public-sector research organisations.
• Career support: students can access departmental career services, industry networking events, internships and collaborative projects with Boulder’s strong technology ecosystem.

Why study at University of Colorado Boulder

CU Boulder is known for active research groups across machine learning, systems, cybersecurity and HCI, providing strong faculty supervision and opportunities to join funded projects. The department fosters interdisciplinary collaboration with engineering, cognitive science, physics and business, which is valuable for students seeking cross-cutting applications of computing and information science.

• Research environment: access to research centres and labs, opportunities for graduate students to publish and present work, and close engagement with faculty pursuing cutting-edge topics.
• Location and industry links: Boulder and the wider Denver metro area host a vibrant technology and startup community, offering internships, industry partnerships and employment opportunities for graduates.
• Facilities and resources: modern computing facilities, HPC resources, and collaboration spaces that support both individual research and team-based projects.
• Flexible pathways: options for thesis or coursework tracks, interdisciplinary electives, and pathways to further research or immediate industry employment.