UC Riverside Adds New Graduate Degree with Data Science Specialization
|Richard Harris in Developer Jobs Thursday, May 26, 2016|
The University of California Riverside (UCR) has added a Data Science specialization to its Online Master of Science in Engineering, a fully online degree program that is aimed at professionals in multi-disciplinary data-driven looking to enhance their careers.
This specialization provides the knowledge to understand, process and analyze large volumes of data, find patterns within the data and extract statistically significant information from them. This covers combined techniques from a multidisciplinary range of subjects to provide the skills needed to interpret large data in text, image and binary forms, use visualization and statistical techniques to interpret and develop mathematical models to express them. Topics within the specialization include data mining, machine learning, statistical computing, and data visualization.
The program has been jointly developed by UCR faculty and NASA’s Jet Propulsion Laboratory (JPL) science staff. The development of the Data Science specialization is being supported by a NASA Minority University Research and Education Project (MUREP) ‘Fellowships and Internships in Extremely Large Data Sets (FIELDS)’ grant awarded to UCR in 2015.
The course material for the online master’s program is equivalent to the traditional master’s program, but with a greater emphasis on technical skills rather than research. Recorded courses, which maintain the same University of California standards as traditional courses, are available for students to watch at convenient times. Students are required to take nine courses for a total of 36 units to graduate, which can be completed in as little as 13 months.
Applications are accepted based on work experience, college coursework completed, GPA, professional certifications, reference letters and GRE scores. The cost of the program is $3,333 per course, or $30,000 for the nine-course program.
Read more: http://www.msol.ucr.edu/
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