The Master of Science in Data Science program, offered by the College of Science 's Department of Computer Science and Department of Mathematics and Statistics , provides students with a Bachelor's degree in the sciences or engineering with foundational knowledge, experience, and skills that are crucial for a data science career. It features a multidisciplinary curriculum in applied math, statistics, computer science, and their intersection - machine learning. Its rigorous, balanced coursework provides students with strong mathematical, computing, and data skills, as well as project experience. Graduates of this program will have the necessary theoretical knowledge, practical data analysis and coding skills for solving complex real-world problems based on massive amounts of data and also meet the qualifications for various data scientist positions in industry and government.
Admission Requirements
Candidates must meet all of the university admission requirements. Students can be admitted in either classified or conditionally classified standing.
To be admitted to classified standing, applicants must have earned a Bachelor's degree in the sciences or engineering from a regionally accredited institution with a minimum GPA of 3.0 (based on a 4.0 scale), and have completed all program prerequisites listed below. Two to three letters of recommendation are also required. The GRE General Test score must also be submitted along with the packet. There is no minimum requirement, but the GRE score will be used to compare and rank applicants. To enter this program with classified standing, a student must have passed the following prerequisites courses (with a C- or better OR the listed required grade below):
- Three semesters college-level calculus courses - differential calculus (e.g., MATH 30 at SJSU), integral calculus (e.g., MATH 31 at SJSU), and a multivariable caluculus course (e.g., MATH 32 at SJSU), with a grade of B or better on the multivariable calculus course.
- A linear algebra course (e.g., MATH 39 at SJSU), with a grade of B or better.
- A discrete math course (e.g., MATH 42 or CS 42 at SJSU).
- An upper-division calculus-based statistics course (e.g., MATH 161A at SJSU), with a grade of B or better.
- A probability theory course (e.g., MATH 163 at SJSU), with a grade of C or better.
- Two CS introductory courses on programming and data structures (e.g., CS 46A and CS 46B at SJSU).
- An upper division data structures and algorithms course (e.g., CS 146 at SJSU), with a grade of B or better.
- An advanced course in object-oriented programming (e.g., CS 151 or CMPE 135 at SJSU) or two semesters of statistical programming coursework, (e.g., MATH 167R and MATH 167PS at SJSU).
Applicants from countries in which the native language is not English must submit TOEFL scores. Minimum TOEFL scores acceptable for admission are 575 (Paper-based), 240 (Computer-based), or 90 (Internet-based).
Advancement to Candidacy
Students may advance to candidacy after completing all admission conditions and all prerequisites for the culminating experience including the Graduation Writing Assessment Requirement (GWAR) .
Requirements for Graduation
University Graduation Requirements
Students must complete all residency, curriculum, unit, GPA, and culminating experience requirements as outlined in the Graduation Requirements section of the Graduate Policies and Procedures .