Doctor of Science in Computer Science
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, data science and application design.
Enjoy Flexibility – 20 courses with start dates every 2 weeks
Affordable Monthly Payments
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.
For more information about the program, see the Academic Catalog.
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 of professional programming work using an OOP language, they will be allowed to start the program with RSH906. 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:
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RSH906 - Technology and Innovation Management
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RSH900 - Doctoral Writing and Inquiry into Research
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DCS901 - Discrete Mathematics for Computer Scientists
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DCS902 - Concurrent and Distributed Systems
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RSH901 - Techniques and Interpretation for Advanced Statistical Research
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DCS903 - System Metrics & Risk Management
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RSH910 - Research Design and Methodology
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DCS904 - Modern Compiler Design
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DCS905 - Simulation and Modeling
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DCS906 - Automata Complexity Theory
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RSH912 - Introduction to the Dissertation
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DCS907 - Algorithm Design
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DCS908 - Computer Ethics
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DCS909 - Artificial Intelligence
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RSH916 - Problem-Based Research in Action
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DIS995 - Dissertation I: Concept Paper and Doctoral Committee Selection
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DIS996 - Dissertation II: Literature Review
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DIS997 - Dissertation III: Methodology and Ethics
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DIS998 - Dissertation IV: Research and Results
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DIS999 - Dissertation V: Conclusion and Oral Defense
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 CreditsRequired Books
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 CreditsRequired 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 CreditsRequired 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 CreditsRequired 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 CreditsRequired 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 CreditsRequired Books
This course begins to ask the doctoral student to reflect on past courses, studies and articles that support and build upon personal areas of interest. The course is designed to challenge students to think about an area of interest and begin develop a comprehensive research topic aligned with their professional goals. Students expand on the research topic, identify appropriate theories, methodologies and consider research design. At the end of eight weeks, students will frame the beginning of a doctoral research dissertation.
3 CreditsRequired 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 CreditsRequired 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 CreditsRequired 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 CreditsRequired Books
This course provides the student with an overview of each part required in the completion of the dissertation writing process. It reflects each of the five chapters necessary when preparing the doctoral dissertation and includes the ethical and professional requirements to help make the author accountable and reflective in its presentation, validity, and significance to future researchers and readers. The student selects an existing, published dissertation in their discipline and examines it throughout the course as a model for how to effectively design and write a solid dissertation.
3 CreditsRequired 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 CreditsRequired 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 CreditsRequired 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 CreditsRequired Books
This course is designed to provide students with additional research tools used to solve everyday problems through a process of inquiry and developing solutions to significant problems in the workplace. This useful strategy can provide the leader a design for decision-making based on data and supportive research. This course satisfies the Proctored Exam requirement for this program.
3 CreditsRequired 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 CreditsRequired Books
This course will focus on the second chapter of the dissertation, the Literature Review. The Doctoral student will expand on the annotated bibliography that they 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 CreditsRequired Books
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 CreditsRequired Books
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 CreditsRequired Books
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