Earn Your Degree from University of Fairfax
Master of Science in Cloud Computing
The Master’s degree is awarded upon the successful completion of a minimum of 36 credit hours. Students have the option of completing a thesis or graduate project/paper. The Master of Science in Cloud Computing prepares graduate students to:
- Have specialized training in a concentrated field of study and develop professional attributes that include communication skills, and ethics to deal with the impact of technology in a global and societal context.
- Encourage independent thinking and creativity that prepares students to pursue industry jobs in the field of Computing and IT or related disciplines.
Degree Program Outcomes
Upon completion of this degree program, students will be able to:
- Demonstrate knowledge of fundamental concepts for graduate study in Cloud Computing.
- Demonstrate knowledge of advanced topics in Cloud Computing.
- Apply design and analysis methods to solve emerging Cloud Computing and related problems.
- Apply basis and advanced concepts associated with Cloud Computing and related fields.
- Conduct research and/or comprehensive projects in Cloud Computing and appreciate the importance of life-long self-learning.
- Argue the basic and advanced concepts associated with Cloud Computing or related field.
- Evaluate and assess the impact of cloud computing on service management.
- Design effective cloud computing solutions that consider an organization’s structure, communications, and operational business processes, as well as financial management and cost model implications.
The Master of Science in Cloud Computer degree program consists of 36 semester credits.
MSCC5100: Cybersecurity Law and Ethics
Overview of cybersecurity and privacy, including cryptography, authentication, malware, viruses, network security, anonymity, privacy and online privacy, risk management; common cyberattacks and techniques for detection and defense; policy and legal perspectives for managing cybersecurity missions supporting private sector and government; cyber technologies as applied to the stability of global information and communications infrastructure; government cybersecurity policies. (3 credits)
MSCC5200: Cloud Application Architecture
Cloud application design guidelines and software patterns. Survey of cloud services for scalable secure cloud applications. Trade-offs in cloud application design, container vs virtual machine deployments, and monolithic vs microservice. (3 credits).
MSCC5300: Research Methods
In this course, the students will learn the basic skills that are essential to becoming a successful researcher. The objective of the course is to teach research skills in a systematic fashion, early in a student’s graduate program. Lecture topics will include research methodology, experimental design, professional ethics and academic integrity, and oral and written presentation techniques. Students will be required to perform a literature survey (on a topic in their own research area), construct a research proposal that includes an experimental design, and write a paper summary in the style of a formal scientific paper. (3 credits)
MSCC5400: Big Data and Cloud Computing
This course covers a wide range of research topics related to big data and cloud computing, including data centers, virtualization, hardware, and software architecture, as well as system-level issues on performance, energy efficiency, reliability, scalability and security. (3 credits)
MSCC5500: Secure Cloud Computing
The course provides a comprehensive guide to security concerns and best practices for cloud computing and cloud services. Topics discussed include cloud computing architectures, risk issues and legal topics, data security, internal and external clouds, information security frameworks and operational guidelines. (3 credits)
MSCC5600: Applied Data Analytics
Applied and practical data analytics. High-level theory, with primary focus on practical application of a broad set of statistical techniques needed to support an empirical foundation for Computing and IT. Introduction to data analytics introduces you to the basics of data science and data analytics for handling of massive databases. The course covers concepts data mining for big data analytics and introduces you to the practicalities of map-reduce while adopting the big data management life cycle. (3 credits)
MSCC5700: Applied Machine Learning for Computing and IT Professionals
This course emphasizes learning algorithms and theory including concept, decision tree, neural network, computational, Bayesian, evolutionary, and reinforcement learning. The course will give the student the basic ideas and intuition behind modern machine learning methods as well as a bit more formal understanding of how, why, and when they work. The underlying theme in the course is statistical inference as it provides the foundation for most of the methods covered. (3 credits)
MSCC5800: Program and Project Management
Problems in managing projects; project management as planning, organizing, directing, and monitoring; project and corporate organizations; duties and responsibilities; the project plan; schedule, cost, earned value and situation analysis; leadership; team building; conflict management; meetings, presentations, and proposals. (3 credits)
MSCC5900: Management and Compliance in Cloud Computing
Maintaining compliance in the cloud. Theory, methodology, and procedures related to cloud computing; proper audit procedures for discovering system vulnerabilities; documenting findings according to the standards of compliance-based auditing. (3 credits)
MSCC6000: Cloud Migration Strategy
Migrating traditional IT services to a cloud-based environment. Technical and business considerations necessary to develop an effective cloud migration strategy for an organization. Decision analysis framework to prioritize migration applications. (3 credits)
MSCC6100: Thesis/Graduate Research Paper
(Prerequisite: Must be taken in last term and all other courses completed) Thesis. (6-0) Credit 6 semester hours. A candidate for the Master of Science in Electrical Engineering is required to perform a study, a design of investigation, under the direction of a faculty advisory committee. A written thesis is required to be presented, defended orally and submitted to the faculty advisory committee for approval. (6 credits)
Credits required for MSCC: 36
University of Fairfax incorporates
into the Master of Science in Cloud Computing curriculum.
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