The Master of Engineering in Cloud Computing Management offers a comprehensive curriculum, covering the technical aspects of cloud computing and related trends like big data, as well as the business skills to implement cloud migration and governance strategies.
The program is designed for current and aspiring business and IT leaders who want to hone their expertise with a focus on cloud architecture, applications and data. Graduates of the program will be able to effectively optimize current cloud deployments, better plan for future investments in cloud technology and manage cloud migrations of any scale.
The online format offers the advantage of synchronous or asynchronous delivery, allowing students the flexibility to study when and where it works best for their situations. While students are encouraged to attend and participate, all live lectures are recorded and can be viewed at a later time if needed.
M.Eng. in Cloud Computing Management Required Courses
CSCI 6012 Cybersecurity and Privacy
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 the private sector and government. Cyber technologies as applied to the stability of global information and communications infrastructure; government cybersecurity policies.
CSCI 6018 Cloud Applications Architecture
Introduction to cloud application design guidelines and software patterns. The course will provide a survey of cloud services and how they can be used to construct scalable, secure cloud applications. Students will learn to understand trade-offs in cloud application design such as selecting container vs virtual machine deployments, monolithic vs microservice application architectures, as well as new paradigms such as serverless computing. Students will evaluate cloud application architectures and communication frameworks to understand their reliability, efficiency, performance and security.
ECE 6005 Computer Architecture and Design
Advanced topics in computer architecture and design; instruction-level parallelism, thread-level parallelism, memory, multithreading and storage systems.
ECE 6130 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. Prerequisites: ECE 6005 or ECE 6105
ECE 6132 Secure Cloud Computing
Security concerns and best practices for cloud computing and cloud services; cloud computing architectures, risk issues and legal topics; data security; internal and external clouds; information security frameworks and operations guidelines.
EMSE 6767 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 systems engineering and engineering management. A variety of practical visualization and statistical analysis techniques. Leveraging Minitab and Excel to examine raw data to arrive at insightful conclusions.
EMSE 6769 Applied Machine Learning for Engineers
A broad introduction to fundamental concepts and techniques in machine learning from the perspective of the systems engineer. The field of machine learning explores algorithms that can learn from examples (e.g. experience) without pre-programmed rules or that can make predictions based on automated analysis of prior data. This course provides students with knowledge of the theory and practice of machine learning, leveraging an open source framework to explore the ideas, algorithms and techniques without a prior background in programming. Topics covered in the course include the relationship between data mining and machine learning, machine learning and statistics, fundamental concepts (preparing/cleansing input data, attribute selection, sampling), linear models, clustering, training/testing/cross-validation, decision trees, probabilistic methods, deep learning, autoencoders, convolutional neural networks and ensemble learning methods.
EMSE 6820 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.
SEAS 6411 Management and Compliance in Cloud Computing
Introduction to different approaches of maintaining compliance in 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. Explore the legal and regulatory environments related to cloud computing concerns. Formulate policy and conduct analysis for the prevention of intrusions, attacks and threats to cloud data. Gain an understanding of the value provided by regulatory, policy and compliance guidelines in addition to pure technology options. Prerequisite: ECE 6132
SEAS 6412 Cloud Migration Strategy
An analysis of migrating tradition IT services to a cloud-based environment. This course will help students analyze the technical and business considerations necessary to develop an effective cloud migration strategy for an organization. Students will use a decision analysis framework to prioritize applications for migration to the cloud, discuss how cloud migration affects operations and staffing and analyze the pros and cons of different migration approaches (i.e., lift and shift, refactoring, redevelopment, retirement). This course introduces a framework for choosing the “best fit” cloud approach for your organization, including decision models for selecting from cloud service models (i.e., IaaS, PaaS, SaaS), deployment models (i.e., private/on-premise, community, public, hybrid), emerging cloud models and options for multi-cloud service brokerage. Prerequisite: ECE 6132
To learn more about GW’s online graduate programs in cybersecurity and cloud computing, and download a free brochure, fill out the fields below. If you have any additional questions, please call (833) 330-1454 to speak to an admissions counselor.
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