National University

What you'll study

The curriculum combines core advanced topics and a dissertation sequence. Core requirements are 11 courses (33 semester credit hours) covering a broad set of subjects including:

• Foundations of computer science: algorithms, programming languages, automata, theory of computation, neural networks, AI and human interaction, plus breadth topics such as cloud computing and data communications.
• Advanced programming languages and algorithms: theory and implementation of language design and algorithm analysis.
• Networks and communications: network concepts, design for reliability/availability/confidentiality, monitoring, multi-cloud, satellite, 5G/6G and quantum data communications considerations and related security techniques.
• Statistics for technology leaders: advanced statistical analyses for information systems and technology research and producing technical output reports.
• Artificial intelligence: intelligent agents, natural language processing, AI performance and integration, and preparing AI project plans for enterprise solutions.
• Security and cybersecurity fundamentals: governance, compliance, people and technology risks, mitigation strategies and defensive resource planning.
• Data and databases: advanced database management systems, data warehouses, data transformation, corruption prevention and business intelligence support.
• Data mining: techniques to discover patterns, trends, anomalies and associations to advance scientific knowledge and performance.

The program also requires dissertation research culminating in submission of an approved final manuscript (original unbound and electronic copy). The PhD requires at least 60 semester credit hours overall; additional credits may be assigned to complete dissertation research. If dissertation deliverables are not met in a course, continuation courses (B, C, and D) may be required; failure to meet deliverables by the end of the D course can result in dismissal. For more detail the institution refers applicants to its Doctoral Student Experience (DSE) Manual.

Entry requirements

Admissions information on the page includes a $0 application fee and states there are no essays or exams required at application. The University may accept up to 12 semester credit hours in transfer for graduate coursework completed at an accredited institution with a grade of B or better. The program requires a minimum GPA of 3.0 (B) for degree completion and official transcripts on file for any accepted transfer credits.

Career prospects

The program frames itself as preparing graduates to work at the intersection of advanced computing, research, and applied technology leadership. Course coverage in AI, networks, security, data management, statistics and algorithms supports roles that require technical depth and research capability; students build a portfolio of work and a dissertation that can be used to demonstrate expertise to employers, academic settings, or industry research groups.

Scholarships & funding angle

The program page does not list specific scholarships or funding amounts. Prospective students should check the university’s financial services and graduate funding pages for institutional scholarships, assistantships, loans, and external fellowship opportunities. Note that all financial obligations must be met before a diploma or degree is issued or posted to the transcript.