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Doctor of Philosophy in Computer Science (PhD-CS)

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100% Online PhD-CS

Complete your studies on your own time.

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40 Months to your PhD-CS

Finish your PhD-CS in just 20 courses.

National and Northcentral have merged, and this program is now offered by NU. Learn more.

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Doctor of Philosophy in Computer Science

Build a better future in technology with the 100% online Doctor of Philosophy in Computer Science (PhD-CS) degree program at National University. Expand your expertise by studying subjects such as software engineering, artificial intelligence, data mining, and cybersecurity. Your doctoral journey will take you deep into the examination of real-world computational issues and the analysis of advanced computing problems.

Through NU’s PhD-CS program, you’ll be given the opportunity to propose your own research, complete hands-on replication studies, and add to the computer science knowledge base. You’ll build your own portfolio while completing your doctoral studies.

Build a Better Technology Future

National University’s innovative PhD in Computer Science program exposes you to the latest concepts, methods, and technology through cutting-edge courses designed and taught by highly experienced and respected industry experts. 

The Western Association of Schools and Colleges (WASC) accredits public and private schools, colleges, and universities in the U.S.

Course Details

Credit Hours: 60

Courses: 20

Estimated Time to Complete: 40 months

The Doctor of Philosophy in Organizational Leadership (PhD-CS) program can be completed in 60 credits. Each course runs 8 weeks and dissertation courses run 12 weeks.

Course Sequence

The PhD program requires a minimum of 60 credits. Additional credit hours may be allowed as needed to complete the dissertation research. If granted, additional courses will be added to the student degree program in alignment with the SAP and Academic Maximum Time to Completion policies. Students who do not complete their program in accordance with these policies may be dismissed.

All incoming PhD-CS students will complete a required writing assessment during their first course, TIM8101.

In this course, students will study how computer science concepts and theories can be applied and used to solve real-world problems. Students will also be introduced to research in computer science and become acquainted with venues for sharing knowledge in the field. 

In this course, students will explore emerging issues in computer network design and management. Of particular attention will be topics on how mobile computing has changed the way networks are designed and managed.

Organizations depend on distributed systems and parallel computing to achieve the performance and reliability required by their systems. These systems provide organizations with the ability to leverage hardware and software platforms to improve efficiency. During this course, you will research the latest developments in computing concepts, such as instruction level parallelism, task level parallelism, multicore computing, and distributed algorithms. You will complete the course by predicting evolving trends in distributed algorithms and parallel computing.

Data and databases are the foundation of all business systems. Organizations that do not understand the importance of data management are less likely to survive in the modern economy. During this course, you will study advanced concepts of database management systems and data warehouses. You will also research processes and techniques used to improve data repositories, manipulate data, and prevent data corruption. By the end of the course, you will be able to construct, assess, and transform data to improve business intelligence to support informed business decisions.

This course includes methods, means, and processes involved in transforming raw data into useable form for a multitude of analytics. Data curation is a set of processes that transforms, manages, stores, and democratizes data for use for analysts and data scientists through the lifecycle of data. The curation of data enables an organization or researcher to maximize the value of the data and effectively use the transformed data to produce and deliver insights. This course considers data that have been already acquired and integrated into useable repository and focuses on teaching techniques to make those data usable for next steps in developing analytics models.

This course will consolidate a foundation of concepts relating to security and cybersecurity, enabling the successful examination of greater detail and complexity in later courses. You will examine the full range from governance through compliance with laws, through people risks, to technology. Various mitigation options are considered to reduce vulnerabilities, counter threats, and to protect an organization’s data and system assets. You will study the need to protect organizations from future exposures and apply critical thinking and synthesis to motivate the resources needed to defend an organization.

With more application systems and data processed, together with mobile, cloud, and virtual environments all technology system risks increase for security, privacy, compliance issues. While expectations for safety rise, increased complexity and threats make the provision far more difficult and expensive. Record tampering and accidental or intentional exposure are also among the internal risks every enterprise face. During this course, you will learn how to assess, mitigate, and manage risks, threats, and vulnerabilities. You will also study theories, models, standards, and frameworks that aid the effective design, protection mechanisms, practices, and procedures to implement and manage operations within information systems.

This course serves as an extensive exploration of statistics for the technology leader. Included in the course, is an advanced examination of statistical analyses commonly used for information systems and technology research. During this course, you will use different statistical tools to enhance your advanced analytical skills. These statistical analysis skills are required to plan, conduct, and interpret quantitative data to inform enterprise decisions. You will also learn to illustrate and produce technical output reports.

Artificial intelligence is becoming more and more useful in helping solve everyday problems. Intelligent agents and natural language processing have become common in the marketplace. During this course, you will evaluate the impact of artificial intelligence on performance and enterprise resources. You will also expand your ability to improve an artificial intelligence application to address varied user specifications. Finally, you will be able to produce a complete artificial intelligence project plan that will integrate with current and proposed IT solutions for process improvement.

Business processes change continually and require new technology solutions to improve production. Improved technology solutions can speed up processes, increase service delivery speed, and reduce the number of defects. This project-driven technical research course explores the principles and processes needed for the efficient development of software solutions with a focus on software quality design and development. During this course, you will research and suggest models and frameworks to improve software development processes based on different business problems and needs.

This course provides a survey of the different methods used to conduct technology-based research. During this course, you will learn about the research principles and methodologies that guide scientific inquiry in order to develop an understanding of the effects of research on individuals and organizations. Specifically, you will study the scientific research lifecycle, data collection methods, and research design methodology. You will finish the course by selecting a research design methodology to support your research interests through the remainder of your program.

Select one of the three research choices below.

This course is an advanced examination of the theories, concepts, and strategies for managing technology policies while developing and implementing computer science projects. During this final course in the PhD-CS program, before starting the dissertation sequence, you will research and design an information technology policy strategy for software development and implementation. You will also evaluate ways to improve the competitive position of an organization, recommend coding control structures for data integrity and security, and plan ways to address business concerns regarding the adoption of new technologies.

The Pre-Candidacy Prospectus is intended to ensure students have mastered knowledge of their discipline prior to candidacy status and demonstrated the ability to design empirical research as an investigator before moving on to the dissertation research coursework. Students will demonstrate the ability to synthesize empirical, peer reviewed research to support all assignments in this course. The Pre-Candidacy Prospectus is completed only after all foundation, specialization, and research courses have been completed.

Students in this course will be required to complete Chapter 1 of their dissertation proposal including a review of literature with substantiating evidence of the problem, the research purpose and questions, the intended methodological design and approach,  and the significance of the study. A completed, committee approved (against the minimum rubric standards) Chapter 1 is required to pass this course successfully. Students who do not receive approval of Chapter 1 to minimum standards will be able to take up to three supplementary 8-week courses to finalize and gain approval of Chapter 1.

Students in this course will be required to work on completing Chapters 1-3 of their dissertation proposal and receive committee approval for the Dissertation Proposal (DP) in order to pass the class. Chapter 2 consists of the literature review. Chapter 3 covers the research methodology method and design and to includes population, sample, measurement instruments, data collection and analysis, limitations, and ethical considerations. In this course, a completed, committee-approved Chapters 2 and 3 are required and, by the end of the course, a final approved dissertation proposal (against the minimum rubric standards). Students who do not receive approval of the dissertation proposal will be able to take up to three supplementary 8-week courses to finalize and gain approval of these requirements.

Students in this course will be required to prepare, submit, and obtain approval of their IRB application, collect data, and submit a final study closure form to the IRB. Students still in data collection at the end of the 12-week course will be able to take up to three supplementary 8-week courses to complete data collection and file an IRB study closure form.

In this dissertation course students work on completing Chapters 4 and 5 and the final Dissertation Manuscript. Specifically, students will complete their data analysis, prepare their study results, and present their findings in an Oral Defense and a completed manuscript. A completed, Committee approved (against the minimum rubric standards) Dissertation Manuscript and successful Oral Defense are required to complete the course and graduate. Students who do not receive approval for either or both their Dissertation Manuscript or defense can take up to three supplementary 8-week courses to finalize and gain approval of either or both items as needed.

**Students select one research methods and one directed research course based on their own research proposal. 

Option 1: Quantitative Research

The results of technical research are frequently used to support informed management decisions. This course provides technology leaders and professionals with the skills needed to design and conduct quantitative research studies to support specific types of data. During this advanced course in research, you will explore and apply different types of quantitative research methods and statistical techniques. You will also explore instrumentation, data collection, and data analysis tools and techniques to create aligned, ethical, and substantive research designs.

A quantitative research design includes objective analysis using experimental, quasi-experimental, and related techniques. Technical quantitative research involves statistical analysis of data collected from a larger number of participants to determine an outcome that can be applied to a general population. During this course, you will work through the scientific research process and apply your knowledge of quantitative research design to develop a technical research proposal in which you can use to support your research interests through the remainder of your program.

Option 2: Qualitative Research

The results of qualitative research are frequently used to support informed management decisions. This course provides technology leaders with an in-depth introduction to qualitative methods for studying human behavior, including grounded theory, narrative analysis, and case studies. During this advanced course in research, you will apply qualitative research methods to an information technology-based study. You will also deepen your research knowledge and skills by conducting interviews, collecting and coding data, producing ethical data conclusions, and creating objective research reports.

A qualitative approach to research of a technical nature integrates theoretical, conceptual, and empirical constructs with common practices and experience to gain an understanding of performance and functionality, develop an applied and testable model for improvement, or provide insights into problems to develop new ideas. During this course, you will work through the scientific research process and apply your knowledge of qualitative research design to develop a technical research proposal to support your research interests through the remainder of your program.

Option 3: Constructive Research

The results of technical research are frequently used to develop new products and services. This course provides technology leaders and professionals with the skills needed to design and conduct constructive research studies based on theory. During this advanced course in research, you will examine the methods and measurements used to design constructive research studies to develop sound technical solutions or prototypes. You will also explore software and security testing tools and user acceptance testing methods in order to create aligned, ethical, and substantive research designs.

Technical constructive research focuses on models, frameworks, tools, and software used by industry to improve value creation. A constructive approach to research of a technical nature integrates theoretical and empirical constructs with common practices and experience to develop an applied and testable model to improve the fields of computer science and information technology. During this course, you will work through the scientific research process and apply your knowledge of constructive research design to develop a technical research proposal in which you can use to support your research interests through the remainder of your program.

Degree and Course Requirements

The University may accept a maximum of 12 semester credit hours in transfer toward the doctoral degree for graduate coursework completed at an accredited college or university with a grade of “B” or better.

The PhD-CS degree program also has the following graduation requirements:

  • A minimum of 48 credit hours of graduate instructions must be completed through NU
  • GPA of 3.0 (letter grade of “B”) or higher
  • Submission of approved final dissertation manuscript to the University Registrar, including the original unbound manuscript and an electronic copy
  • Official transcripts on file for all transfer credit hours accepted by the University
  • All financial obligations must be met before the student will be issued their diploma and/or degree posted transcript.

The PhD-CS degree prepares you for computer science positions within a variety of data, technology, manufacturing and service sectors. Through a deep examination of real-world computational issues and analysis of advanced computing problems, you’ll expand your expertise in software engineering, artificial intelligence, data mining, and cybersecurity. These skills will qualify you to pursue a range of occupations that include:

  • Data Scientist
  • Software Developer
  • Systems Engineer
  • Machine Learning Engineer
  • Post-secondary Computer Science Educator

According to Emsi labor market analytics and economic data1, computer science careers span a variety of technology, manufacturing, and service settings, including:

  • Defense Manufacturing and Services
  • Computer and Information Technology
  • Financial Services
  • Colleges and Universities

SOURCE: Emsi Labor Analyst- Report. Emsi research company homepage at (Report viewed: 4/19/2022). DISCLAIMER: The data provided is for Informational purposes only. Emsi data and analysis utilizes government sources to provide insights on industries, demographics, employers, in-demand skills, and more to align academic programs with labor market opportunities. Cited projections may not reflect local or short-term economic or job conditions and do not guarantee actual job growth. Current and prospective students should use this data with other available economic data to inform their educational decisions.


Faculty assists each NU Doctoral student to reach this high goal through a systematic process leading to a high-quality completed dissertation. A PhD dissertation is a scholarly documentation of research that makes an original contribution to the field of study. This process requires care in choosing a topic, documenting its importance, planning the methodology, and conducting the research. These activities lead smoothly into the writing and oral presentation of the dissertation.

A doctoral candidate must be continuously enrolled throughout the series of dissertation courses. Dissertation courses are automatically scheduled and accepted without a break in scheduling to ensure that students remain in continuous enrollment throughout the dissertation course sequence. If additional time is required to complete any of the dissertation courses, students must re-enroll and pay the tuition for that course. Continuous enrollment will only be permitted when students demonstrate progress toward completing dissertation requirements. The Dissertation Committee determines progress.

Program Learning Outcomes

As a graduate of National University’s Doctor of Philosophy in Computer Science (PhD-CS) program, you’ll be able to:

  • Develop knowledge in computer science based on a synthesis of current theories
  • Explain theories, applications, and perspectives related to computer science
  • Evaluate theories of ethics and risk management in computers and emerging technologies
  • Formulate strategies for managing computing resources in global organizations
  • Contribute to the body of theory and practice in computer science


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To apply to the Doctor of Philosophy in Computer Science (PhD-CS) degree program, you must have a conferred master’s degree from a regionally accredited academic institution.

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Program Disclosure

Successful completion and attainment of National University degrees do not lead to automatic or immediate licensure, employment, or certification in any state/country. The University cannot guarantee that any professional organization or business will accept a graduate’s application to sit for any certification, licensure, or related exam for the purpose of professional certification.

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