Data Science
Overview
Develop the Knowledge to Decode Big Data
Prepare yourself to become a leader in the growing field of data analysis with a Master of Science in Engineering in Data Science from the University of California, Riverside. The online Master of Science in Engineering with a specialization in Data Science can teach you to distill valuable insights from sizable amounts of data.
Coursework is designed to allow graduates to develop efficient techniques to identify, analyze and visualize hidden patterns within data groups to extract critical information.
Graduate in as few as 13 months
No residency requirement
Enjoy flexible admissions and three start dates
Why a Master’s Degree in Data Science Online?
We live in a time when the world’s citizens effortlessly create enormous amounts of data that require storage and analyzation. From simple texts and videos to private financial and medical data, the demand for professionals with data science and analytical skills has created many lucrative possibilities.
IT data scientists can work for a variety of companies, such as IBM, American Express and Amazon.
According to career site Glassdoor.com, data scientists can earn approximate annual salaries of $100,000 to $130,000, while data visualization specialists’ base earnings start around $80,000 and can reach $100,000.
Employment for data scientists is expected to grow 11% from 2014 to 2024, faster than the average for all occupations.*
**Glassdoor.com
Who should choose a Data Science Master’s?
Curriculum
The online Master of Science in Engineering is a comprehensive engineering program that encompasses both leadership strategy and technical skills. Coursework includes 16 credits of core engineering classes, plus 16 credits within your specialization, helping you tailor the program to your area of expertise.
To accommodate busy professionals, the online Master of Science in Engineering does not include a required residency. Instead, students participate in 4 one-credit capstone courses throughout the program, providing a rich learning experience that comes with maximum flexibility.
MSEDS Core Courses / 16 credit hours
Engineering in the Global Environment (4)
Technology Innovation and Strategy for Engineers (4)
Introduction to Systems Engineering (4)
Principles of Engineering Management (4)
*Curriculum subject to change
Data Science Specialization / 16 credit hours
Choose 4 from the following options
Foundations of Applied Machine Learning (4)
Application of Visualization in Data Science (4)
Data Mining Techniques (4)
Advanced Computer Vision (4)
Statistical Computing (4)
Statistical Mining Methods (4)
Machine Learning (4)
Information Retrieval & Web Search (4)
Data Visualization & Big Data Tools (4)
Admission Requirements
The following criteria are considered during the admission process for the M.S. in Engineering program:
- A bachelor’s degree in engineering or related field from an accredited institution.
- Official transcripts.
- GPA.
- GRE/FE scores.
- TOEFL or IELTS scores (for international applicants).
- Evidence of significant professional engineering experience.
- Professional certifications.
- Reference letters.
- Applicants of the bioengineering specialization are expected to have taken a course in Differential Equations.
Careers
Chief Data Officer
E-commerce Data Specialist
Social Media Data Analyst
Student Outcomes
“The knowledge I learned from my classes is very applicable to the work that I do every day. I liked the course content and professors very much. They inspired me to do even more of my own research.”
– Peter Do
Class of 2017
“This program has been one of the best experiences I have ever had. I was so happy when I was accepted into the program because I value the university and its great reputation. The instructors have been exceptional throughout the Master of Science in Engineering – Materials at the Nanoscale program. I felt such great support from everyone throughout the program.
I am so glad I chose this specialization because it connects with the work I do now and I am applying what I have learned.”
– Curt Allen
Class of 2018
“Taking the program online, I was able to do extra research to assist me with grasping the engineering concepts.”
– David Butler
Class of 2016
Faculty
Dr. Tom Fryer
Master’s of Engineering Online
Dan Jeske, Ph.D.
Statistics and Vice Provost
Christian Shelton, Ph.D.
Computer Science and Engineering
Craig Schroeder, Ph.D.
Computer Science and Engineering
Eamonn Keogh, Ph.D.
Computer Science and Engineering
Ravi Ravishankar, Ph.D.
Computer Science and Engineering, and Associate Dean
Vagelis Hristidis Christidis, Ph.D.
Computer Science and Engineering
Salman Asif, Ph.D.
Electrical and Computer Engineering
Amit Roy-Chowdhury, Ph.D.
Electrical and Computer Engineering
Bahram Mobasher, Ph.D.
Physics and Astronomy
James Flegal, Ph.D.
Statistics
Interested in this degree?
The University of California, Riverside’s online Master’s in Data Science Program is ranked #17 by U.S. News & World Report among Best Online Information Technology programs.
The University of California, Riverside is regionally accredited by the Western Association of Schools and Colleges (WASC). Regional accreditation assures students that UC Riverside meets the highest standards in terms of learning opportunities and a commitment to self-improvement.
U.S. News & World Report consistently ranks the University of California, Riverside among the top 3 in the nation for social mobility, an honor that reflects our longstanding commitment to cultural, professional and geographical diversity.
