Doctor of Science in Computer Science
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- Doctor of Science in Computer Science
The Doctor of Science in Computer Science program recruits individuals from diverse settings and communities who seek to become effective technological innovators, who exhibit a foundational knowledge in computer science (e.g. Object Oriented Programming, data structures, analysis of algorithms, and discrete mathematics) and use this knowledge to ask questions and creatively think in order to determine the best uses of technological innovation in a variety of fields and apply technological methods to create systems that benefit and improve business and society.
The mission of the Doctor of Science in Computer Science program is to provide quality education grounded in theoretical and empirical research, in order to prepare students to assume positions as technological innovators in the professional workforce. The program provides an academically rigorous learning environment that encourages creative thought in technical and theoretical issues so that students have the ability to apply their educational foundation in a variety of real-life settings.
The mission of the Doctor of Science in Computer Science program is to provide a deep understanding and systemic ability to apply doctoral-level research and writing, discrete and statistical mathematics, economic and operations theory, technology and innovations management, simulation, modeling, algorithmic design, logic, programming constructs, and automata complexity theory to business and societal topics.
This doctorate program is broad in scope, preparing students in the application, research, analysis, and evaluation of past and emerging computer software design topics and applications.
Throughout the program, students engage in the research, inquiry, and application of computer software design related topics, with a special focus on the evaluation and identification of new possibilities for computer technology and algorithm-based applications. Students work individually and in the learning community setting through applied course projects, assignments, deep research, ideation, cross-disciplinary assignments, and online communications. Completion of the final doctoral project follows a systematic doctoral project model and produces a unique new piece of knowledge of societal value to the field of computer science.
Applicants must meet the general GRADUATE REQUIREMENTS.
Please refer to the University Catalog for Tuition and Fees.
This program is designed to be completed in about 38 months.
For more information about program requirements, completion, and licensure, refer to the University Catalog.
View the course schedule for this program: DSCS Degree Plan.
CORE REQUIREMENTS:
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.
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.
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.
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.
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.
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.
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.
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.
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.
RESEARCH 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. This course satisfies a proctored assessment and residency requirements for this program and is not eligible for transfer credit.
Within an ethical framework, ethical and professional issues affecting the individual, the practice of professional nursing, and the profession will be explored. 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.
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.
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.
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. This course satisfies a residency requirement for this program and is not eligible for transfer credit.
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 a proctored assessment requirement for this program and is not eligible for transfer credit.
DOCTORAL PROJECT COURSES :
This course will begin the Doctoral Project 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. This course is 16 weeks in length. This course satisfies a dissertation requirement for this program and is not eligible for transfer credit.
This course will focus on the second chapter of the doctoral project, 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. This course is 16 weeks in length. This course satisfies a doctoral project requirement for this program and is not eligible for transfer credit.
This course will focus on chapter three of the doctoral project and culminate in a meeting of the Doctoral Student, Institutional Review Board, and the Doctoral Committee for approval of the Doctoral Project Proposal. In this course, the Doctoral student will formulate the third chapter of the doctoral project, 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. This course is 16 weeks in length. This course satisfies a doctoral project requirement for this program and is not eligible for transfer credit.
In this course of the Doctoral Project, students will conduct the research/study portion of the doctoral manuscript 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. This course is 16 weeks in length. This course satisfies a doctoral project requirement for this program and is not eligible for transfer credit.
In this final course of the Doctoral Project, students will be writing the conclusion of the final manuscript, focusing on analysis of the doctoral project research with recommendations for further research. Students will also facilitate and perform the Oral Defense via teleconference. This course is 16 weeks in length. This course satisfies a proctored exam requirement for this program and is not eligible for transfer credit. This course satisfies a doctoral project requirement for this program and is not eligible for transfer credit.