Data Analytics Engineering MS

Duration	1.5-2 Months
Level	Masters Program

The MS in Data Analytics Engineering is a Volgenau multidisciplinary degree program, administered by the Department of Statistics, and is designed to provide students with an understanding of the technologies and methodologies necessary for data-driven decision-making
Students study topics such as data mining, information technology, statistical modeling, predictive analytics, optimization, risk analysis, and data visualization. It is aimed at students who wish to become data scientists and analysts in finance, marketing, operations, business/government intelligence and other information-intensive groups generating and consuming large amounts of data
The masters in data analytics engineering are designed to provide students with an understanding of the technologies and methodologies necessary for data-driven decision-making. Topics cover data mining, information technology, statistical models, predictive analytics, optimization, risk analysis, and data visualization

Class 12th	No specific cutoff mentioned
Bachelors	No specific cutoff mentioned Applicants must have completed a baccalaureate degree from a regionally accredited program with a reputation for high academic standards and an earned GPA of 3.00 or better in their 60 highest-level credits. While no specific undergraduate degree is required, a background in engineering, business, computer science, statistics, mathematics, or information technology, is desirable, or alternatively strong work experience with data or analytics may be used At a minimum at least one course each in calculus, statistics, and computer programming is required. Data Analytics Fundamentals may be required for students without a basic foundation in Data Analytics
Exams	TOEFL: 80 IELTS: 6.5 PTE: 59

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