Computer Science, PhD-TM
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Overview
Providing a broad base of understanding of the foundational technology in any information system, NU’s Computer Science specialization helps students understand how computers function and communicate from the inside out. This specialization dovetails very well with the larger goals of your PhD program. A general specialization, it was created to provide you with a foundation on a wide variety of computing topics and to prepare you for a range of technology leadership roles. On graduation, you will be able to use the general but in-depth knowledge you’ve gained to lead the innovative integration of computer technologies in any organization.
Benefits
Unmatched Flexibility
NU offers weekly course starts, no scheduled lecture hours, no group assignments, weekly assignments, and the ability to schedule courses around your personal and professional obligations.
100% Doctoral Faculty
No matter the degree level you pursue, you can rest assured that you will be mentored by doctors in your field of study.
One-to-One Engagement
You won’t have to fight for face time as one of many within a classroom. At NU, you’ll have the opportunity to interact one-to-one with your professor, receiving personalized mentoring.
Course Details
PHD-CY
Credit Hours : 60
Courses: 20
Estimated time to completion: 50 months
*Credit hours and courses reflect new students meeting credit requirements and utilizing no transfer credits. Est. Time of Completion reflects new students following the preferred schedule designed by the Dean for the program.
Course Name
This course supplies an overview of computer science, setting the baseline for key topics in the field. In this course, you will study the importance of algorithms, the value of diverse languages, and the solutions created within the field. This course will also outline the role of theory, practice, and research in general and within the degree. A breadth of introductory topics will extend to data communications, cloud computing, data, artificial intelligence. The foundations of computer science will survey automata, theory of computation, neutral networks, intelligence, and the importance of human interaction.
Programming languages and algorithms evolve due to changes in technology, needs, security, and other environmental adjustments. Programming must therefore adjust solutions quickly while limiting the use of resources. This course is an advanced study of the practical and theoretical principles behind the design, analysis, and implementation of algorithms and programming languages for research and professional practice. During this course, you will evaluate the practical and theoretical principles behind language development and the use of different programming languages to address programming problems. You will also examine current algorithms and their evolution for resolving common and anticipated computational problems.
This course explores the latest developments and applications of parallel and distributed computing in various domains. The course delves into advanced concepts and techniques related to algorithm optimization, solution-driven architectures, and the impact of parallel and distributed computing on advanced technologies and solutions. You will focus on the specific considerations for parallel computing in Internet of Things (IoT) solutions, advancements in modern parallel computing, applied parallel computing in cybersecurity, and the application of distributed computing in Blockchain technology. Through research, analysis, and assignments, students will gain a deeper understanding of these topics and their real-world applications.
This course addresses needs in industry, business, and academia to improve performance and advance scientific knowledge. You will learn data mining techniques that help discover patterns, trends, anomalies, and associations that are otherwise hidden or unknown. In addition, this course introduces the fundamentals, principles, implementation techniques, and applications of data mining. Learning also includes data curation techniques, focuses on exploratory data analysis, prediction, classification, association analysis, similarity assessment and clustering, outlier, and anomaly detection. Interpreting and evaluating data analysis/data mining results is explored. Additionally, data mining experience for applications in computer vision, big data, and social networks will be provided.
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.
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.
Learning Outcomes
- Contribute to the body of theory and practice in technology management
- Formulate strategies for managing technology and innovation in global organizations
- Evaluate theories of ethics and risk management in computers and emerging technologies
- Communicate with diverse audiences about theories, applications, and perspectives related to technology and innovation
- Develop knowledge in technology and innovation based on a synthesis of current theories
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.
Program availability varies by state. Many disciplines, professions, and jobs require disclosure of an individual’s criminal history, and a variety of states require background checks to apply to, or be eligible for, certain certificates, registrations, and licenses. Existence of a criminal history may also subject an individual to denial of an initial application for a certificate, registration, or license and/or result in the revocation or suspension of an existing certificate, registration, or license. Requirements can vary by state, occupation, and/or licensing authority.
NU graduates will be subject to additional requirements on a program, certification/licensure, employment, and state-by-state basis that can include one or more of the following items: internships, practicum experience, additional coursework, exams, tests, drug testing, earning an additional degree, and/or other training/education requirements.
All prospective students are advised to review employment, certification, and/or licensure requirements in their state, and to contact the certification/licensing body of the state and/or country where they intend to obtain certification/licensure to verify that these courses/programs qualify in that state/country, prior to enrolling. Prospective students are also advised to regularly review the state’s/country’s policies and procedures relating to certification/licensure, as those policies are subject to change.
National University degrees do not guarantee employment or salary of any kind. Prospective students are strongly encouraged to review desired job positions to review degrees, education, and/or training required to apply for desired positions. Prospective students should monitor these positions as requirements, salary, and other relevant factors can change over time.