The Volgenau School of Engineering at George Mason University (GMU) offers an online Master of Science (MS) in Data Analytics Engineering program that provides students with training in data science and data analytics. The program focuses on applications of modern data systems, technologies, and methodologies in a broad range of fields, including finance, marketing, and business operations. It includes core courses in statistics, data management, data mining, data visualization, and decision management, as well as elective courses in areas like digital forensics, financial engineering, business intelligence, and health data analytics. Students must complete a total of 30 credits by taking ten courses in order to meet the program’s graduation requirements, which can be done in a few as 18 months by students enrolled full-time. The program is offered 100% online and does not require any campus visits.
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GMU’s online MS in Data Analytics Engineering program is classified by OnlineEducation.com as both a master’s in data analytics and a master’s in data science program based on its curriculum.
The online MS in Data Analytics Engineering offered by GMU utilizes the Blackboard learning management system (LMS) to deliver lectures and other instructional materials asynchronously. Students in the program can stream lectures, complete assignments, and access other course materials through Blackboard on demand, 24-7. Students can also communicate with course instructors through the school’s LMS. While asynchronous instruction provides students with flexibility in terms of when they access class modules, students in the program are still responsible for meeting deadlines and completing assignments by set due dates.
GMU’s online MS in Data Analytics Engineering program has a curriculum that emphasizes the professional applications of data science and data analytics tools and technologies to inform and improve decision-making in a variety of contexts. Students select five courses from the program’s core curriculum, which includes classes in Analytics: Big Data to Information; Principles of Data Management and Mining; Analytics and Decision Analysis; and Applied Statistics and Visualization for Analytics. As part of the core requirements, students may also complete a self-directed data analytics project. Students may then choose from a range of electives that cover specialized topics in analytics and data science, such as Learning from Data (Machine Learning); Applied Predictive Analysis; Decision Support Systems Engineering; Decision and Risk Analysis; and Data Analytics for Social Media.
GMU is accredited by the Southern Association of Colleges and Schools Commission on Colleges (SACSCOC).
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