Master of Science in Statistical Data Science

The purpose of the program is to deliver a comprehensive curriculum in the fields of statistics and data science to prepare students with diverse backgrounds (including statistics, mathematics, computer science, engineering, and other quantitative fields) for the data science workforce or a doctoral program. The program curriculum emphasizes the following aspects. First, students will be trained in-depth in modern statistical and machine learning techniques in addition to the classical statistics theory and applications. Second, they will learn and polish computational skills for various types of data sets, including large-scale data ubiquitous in business, technology, and science. Third, these two aspects of the program are built on a solid foundation of statistical theory and an understanding of mathematical principles behind techniques and algorithms; this blend is crucial for success in industrial and academic careers in the rapidly changing big data era. Finally, the program has built-in flexibility for different backgrounds and career plans through various electives.

Applicants to the program must:

hold a baccalaureate degree from a regionally accredited institution, or shall have completed equivalent academic preparation as determined by the appropriate campus authority; be in good academic standing at the last college or university attended; have a 3.0 GPA in their earned undergraduate degree or in the last 60 semester (90 quarter) units completed, or have earned a post-baccalaureate degree; have a baccalaureate degree in a quantitative field, including but not limited to statistics, mathematics, computer science, physics, engineering, or relevant fields.

submit a TOEFL score (minimum 550/80) or IELTS score (minimum 7.0) obtained within the past two years if their undergraduate degree is from a country where the official language is not English.?