SDSU's MS in Data Science program has been ranked the Most Affordable Master's in Data Science program in the nation by leading data science website Discover Data Science.
Data science is one of the hottest careers in the nation today, with demand predicted to grow even more in the future. It's common to see it rated as the number one career in the nation on major employment websites such as Glassdoor and CareerCast . The SDSU MS in Data Science is a one-year program that provides graduates with the statistical, mathematical, and computational skills needed to meet the large-scale data science challenges of today's professional world.
The SDSU MS in Data Science program is:
- Innovative: The curriculum incorporates current techniques in statistics, operations research, predictive modeling, data mining, forecasting, big data programming and management, and data visualization.
- Professionally relevant: The program's focus is on application and interpretation of modern data analysis techniques of known value in today's professional world, both private and public sector.
- Professionally valuable: Here is a list of some of the organizations that have hired our department's recent B.S., M.S., and Ph.D. graduates in data science-related capacities.
The SDSU MS in Data Science is a 30 credit program designed to be completed in one calendar year, June through May, although students may take more than one year to complete if they desire. For added convenience, summer courses are available online so that students may start the program online in the summer and complete it on campus during the following academic year. More information on program structure and coursework is available here.
Who should apply?
If you want to use your quantitative talents to make a difference by solving important and challenging problems, this program could be right for you. You don't have to have an undergraduate major in mathematics or statistics to succeed; this program is accessible to people from a wide variety of other undergraduate backgrounds as well, including economics, engineering, computer science, the physical sciences, and many others. Of course, a certain level of background is necessary. More information on admission requirements is available here.