Graduate with the advanced skills central to high-level careers in computer science.

Further your technical abilities and research skills to prepare for careers as technological innovators in the field of computer science.

The Doctor of Science in Computer Science is designed to benefit people from a variety of disciplines by offering a curriculum that focuses on understanding theoretical concepts and practical applications of Computer Science in the context of advanced research and analysis methods in areas related to computer architecture and software design.

Enjoy Flexibility – 20 courses with start dates every 2 weeks
Earn an Affordable Degree – Tuition and fees only $29,900
Pay Monthly – Opt to pay $375 per month
Focus on your Passion – Choose your Capstone

This program aims to equip you with the skills to evaluate existing technologies and applications, identify possible shortcomings, and help identify innovative ways in which they may be improved.

Our doctoral curriculum pairs fundamental research courses such as Technique and Interpretation for Advanced Statistical Research; Doctoral Writing and Inquiry into Research; and Technology and Innovation Management with core courses including Algorithm Design, Artificial Intelligence, and System Metrics and Risk Analysis.

Students pursuing this degree will also take a special series of courses designed to aid them in developing, researching, and writing their doctoral dissertation.

Get in touch to learn more.

Admission Requirements

  • Application – A completed application.
  • Resume – A resume or curriculum vitae.
  • Statement of Goals – A statement of your goals reflecting the academic, professional, and personal goals you would like to achieve through your work with Aspen University. Your goals statement will be evaluated by the Admissions Committee as part of the application process. The statement of goals should be between 300 – 500 words.
  • Computer Science Experience – Students are expected to be competent Object Oriented Programming (OOP) developers who are comfortable using appropriate data structures, algorithm performance concepts, and discrete mathematic principles in their work. If a student can provide official transcripts proving that they have completed an OOP course in the last seven years or recent evidence or professional programming work using an OOP language, they will be allowed to start the program with RSH900. Without evidence of current skill programming using an OOP language building upon computer science principles, students may be required to take a prerequisite course, DCS900 Logic & Programming Constructs, before beginning their doctoral program work.
  • Master’s Degree Transcripts – Official transcript demonstrating a conferred master’s degree from an institution that is accredited by a CHEA recognized accrediting body or an international equivalent, with a minimum cumulative GPA of 3.0 or greater.
  • Military Documentation (Optional) – A copy of the most recent orders; or a copy of DD214 (This can be requested from the National Archives.)

Courses:

    This research course examines the basic principles and techniques of doctoral scholarship, and offers an overview of the development of theory and research logic, explores the relationship between theoretical and empirical constructs, and provides a wide variety of specific research methodologies, including the scholarly publication process. Students study the principles of the scientific method and research design techniques common to both qualitative and quantitative research, including sampling methods and data collection techniques. Material includes examination of various research methods including electronic searches and retrieval methods. Students learn to critically read research papers and articles, and are introduced to the writing techniques necessary to produce expository and analytical papers to the standards of publishable work. This course is a prerequisite for all other doctorate courses.

    3 Credits
    Required Books

    This course is designed to explore the foundations and intricacies of discrete mathematics, exploring the architecture, theory, application, and new possibilities of the topic as it relates to the field of computer science. This course will review and expand on previous mathematical knowledge and introduce discrete mathematical concepts specific to the area of advanced computer science.

    3 Credits
    Required Books

    This course covers the fundamentals of concurrent and distributed systems including threading, synchronization and deadlock prevention as well as logical clocks, group communication and distributed transactions. It also covers current topics such as web services and software for multiprocessors and multicore processors.

    3 Credits
    Required Books

    This course concentrates on the engineering of human-made systems and systems analysis by covering theories, methods, and procedures for creating new systems as well as techniques for improving existing systems. The course introduces a variety of analytical models and methods for accomplishing system analysis as well as addressing the need to properly integrate a variety of engineering design and management disciplines to effectively implement the concepts and principles of systems engineering.

    3 Credits
    Required Books

    With data explosion, data analysis methods using statistics play a fundamental role in the scientific world and industry. Data from multiple sources are common as well. However, we all know that more data does not necessarily imply better information. Extracting valuable information from a mountain of data requires statistical, computational, and analytical skills. Therefore it is imperative for students to learn how to analyze their data using statistics and derive inferences and model the data that is being used in the thesis. Statistics helps researchers perform data analysis using statistical models and inferences. Descriptive statistical analysis summarizes data into charts and tables and does not try to draw any conclusions about the sampled data. It only summarizes the data in a meaningful way for simpler interpretation. However, inferential statistics allows you to analyze the data even further. It allows one to draw conclusions and infer hypotheses using the same data. This course covers the foundations of statistics and data analysis. It helps you know how to ask and answer the right questions and solve the problem correctly by applying statistics. This course also aims to help students understand business issues from a finance, marketing, management, application domain, or accounting perspective, and then figure out how statistics can help solve the problem. This course also focuses on how statistical thinking improves the ability of a manager to run or contribute to a business. 

    3 Credits
    Required Books

    This course is designed to explore the foundations and intricacies of modern computer compilers, exploring the architecture, theory, application, and new possibilities of the topic as it relates to the field of computer science. This course integrates basic compiler construction using pseudo-code with a focus on current changes in the field such as the requirement for compilers to accommodate an increasing diversity of architectures and programming languages.

    3 Credits
    Required Books

    Complex computing applications are launched system wide only after simulation, modeling and testing have been conducted and the results analyzed. This course addresses fundamental issues in developing those processes and prepares students for their own project simulation or model. Students will be able to describe differences in various methods of central tendency, effectively use a variety of methods for data analysis and demonstrate how different testing variables can affect simulations or models.

    3 Credits
    Required Books

    This course is designed to explore the foundations and intricacies of automata complexity theory, exploring the architecture, theory, application, and new possibilities of the topic as it relates to the field of computer science. The theory of computation or computer theory is the branch of computer science, theory, and mathematics that deals with whether and how efficiently a problem can be solved. The field is divided into two major branches: computability theory and complexity theory. This course will introduce theories, terms, and applications relevant in the area of computation as well as require doctoral level research and writing in order to understand the material in the broader context of computer science.

    3 Credits
    Required Books

    This course is designed to explore the foundations and intricacies of algorithm design, exploring the architecture, theory, application, and new possibilities of the topic as it relates to the field of computer science. Algorithm design is a specific method to create a mathematical or theoretical process in solving problems. This course implements exercises to ensure comprehension of algorithm concepts and applications as well as requires research and doctoral level writing on the theoretical problem-solving concepts of algorithm design.

    3 Credits
    Required Books

    This course discusses IT history, with a focus on cultivating an awareness of current issues and a familiarity with ethics. Student will study the ethical theories used to analyze problems encountered by computer professionals in today’s environment. By presenting provocative issues such as social networking, government surveillance, and intellectual property from all points of view, this course challenges students to think critically and draw their own conclusions, which ultimately prepares them to become responsible, ethical users of future technologies.

    3 Credits
    Required Books

    This course design to study the foundations of Artificial Intelligence in modern environment and to instill an understanding of representations and external constraints with the idea of enabling a student to think creatively. Topics include knowledge representation, search strategies, logical and probabilistic reasoning, learning, natural language understanding, expert systems, and computer vision.

    3 Credits
    Required Books

    This course primarily investigates how to design and evaluate research in education. Emphasis in this course is on providing students with the basic information needed to understand the research process from idea formulation through data analysis and interpretation, enabling students to use this knowledge to design their own research on a topic of personal interest and permitting students to read and understand the literature of educational research. Topics include quantitative, qualitative, and mixed research designs; and applications specific to education and scholarly research.

    3 Credits
    Required Books

    Provides a cross-functional framework for analyzing organizational problems, examines economic research, and applies research inferences to decision making. Integrates the topics of strategy and organizational architecture to explore the theory of business and environmental management. Investigates corporate policy, finance, accounting, marketing, information systems, operations, compensation, and human resources, and focuses on the interrelationships and coordination needs to do business. Explores the theoretical roots of competing policy options and assesses implications of business decisions and various regulations as they affect the productivity and overall performance of the private sector.

    3 Credits
    Required Books

    Explores the fundamental issues and recent developments in operations management, including manufacturing and service management, supply chain management, and project and systems management. Learners investigate the role of operations and supply chain management, and the interactions of these business activities with other functional areas within the firm. In addition, students examine contemporary issues related to total quality management, just-in-time systems, supply and value chains, reengineering, and other business improvement processes. Case methods and review and analysis of pertinent scholarly and practitioner research are used to enhance the learning experience and assist students to develop a framework for understanding, analyzing and addressing operations and supply chain management issues.

    3 Credits
    Required Books

    Provides an integrated, strategic view of management of technology. Focusing on theory and practice, the course addresses the contemporary challenges general managers face today; e.g., globalization, time compression, and technology integration. Explores several strategic approaches for dealing with these challenges, both from a managerial and from an economic viewpoint. Concepts presented will be especially valuable for chief technology officers, directors of technology, chief information officers, and management personnel in R&D, product development, and operations.

    3 Credits
    Required Books

    This course will begin the Dissertation process by guiding the Doctoral student through the selection of the Doctoral Committee. After the selection of a Committee Chair and committee members, the doctoral student will begin selection of a dissertation topic and formulation of the Concept Paper. The formulation of the Concept Paper will provide a foundation for the first three chapters of the dissertation. Doctoral students will work closely with their Committee Chair to determine an appropriate dissertation topic.

    3 Credits
    Required Books
    Prerequisites: Comprehensive Proctored Exam

    This course will focus on the second chapter of the dissertation, the Literature Review. The Doctoral student will expand on the annotated bibliography that he/she included in the Concept Paper to create a narrative literature review that provides a theoretical and conceptual framework for the dissertation study and places the topic of study in its proper context in time by covering the historical data available on the topic in scholarly literature while creating a foundation for the doctoral student’s conclusions that will be drawn from the study and grounded in existing literature.

    3 Credits
    Required Books
    Prerequisites: DIS995 Comprehensive Proctored Exam

    This course will focus on chapter three of the dissertation and culminate in a meeting of the Doctoral Student, Institutional Review Board, and the Doctoral Committee for approval of the Dissertation Proposal. In this course, the Doctoral student will formulate the third chapter of the dissertation, including the research procedure that will be used in the study, the methods which will be used to obtain research results, and the proposed methods for data analysis. This course will also cover ethics in research, concerning the use of human subjects, and provide the Doctoral Student with proper procedures for obtaining approval for his/her research methods and successfully completing an ethical research study.

    3 Credits
    Required Books
    Prerequisites: DIS996 DIS995 Comprehensive Proctored Exam

    In this course of the Dissertation, students will conduct the research/study portion of the dissertation while adhering to ethical standards as well as formulate the fourth chapter of the dissertation. The fourth chapter on communicating the facts obtained through research in an organized way so that the reader can assess the results of the study on his/her own.

    3 Credits
    Required Books
    Prerequisites: DIS997 DIS996 DIS995 Comprehensive Proctored Exam

    In this final course of the Dissertation, students will be writing the Conclusion of the Dissertation. This chapter focuses on analysis of the Dissertation research with recommendations for further research. Students will also facilitate and perform the Oral Defense via teleconference. Upon successful completion of the Oral Defense, students will apply for publication of the Dissertation.

    3 Credits
    Required Books
    Prerequisites: DIS998 DIS997 DIS996 DIS995 Comprehensive Proctored Exam