Applied Data Science Department
MS - Data Analytics
The MS in Data Analytics degree program provides students from diverse academic and professional backgrounds with the advanced education necessary to draw insights from real data and to apply analytical skills to real-world problems. This program prepares students to conduct high-volume data management, predictive analytics, and data visualization toward solving real problems in their specialized career domains. Its multidisciplinary curriculum draws on insights from mathematics and statistics, computer sciences and software engineering, business management, health science, social science, and the natural sciences. Students completing the degree will have a practical knowledge of data analytics and the ability to apply appropriate statistical analyses and machine learning techniques needed to identify patterns, make predictions, design visualizations, and communicate findings effectively.
This Special Session degree program is offered through the College of Professional and Global Education (CPGE). It is a hybrid program consisting of ten courses with both in-person and fully online modes.
For Program Information visit: www.sjsu.edu/msda
Admission to University
Candidates must apply through the CSU admissions portal, Cal State Apply, and meet all university admissions requirements. Applicants will need to apply separately to the university to obtain approval for university-level admission and to CPGE to obtain admission into the MS in Data Analytics.
In addition to holding a bachelor's degree as required above, international applicants (or applicants who earned their degrees in a country where the primary language is not English) must achieve a minimum English-language proficiency test score as indicated on the Graduate Program Test Requirements webpage at GAPE.
Admission to Program
Candidates must meet all the university admission requirements. Students can be admitted in either classified or conditionally classified standing. To be admitted to classified standing, the successful applicant must have earned a bachelor's degree from a regionally accredited institution and achieved a GPA of at least 3.0 (on a 4.0 scale) in the bachelor's degree institution or in the last 60 semester or 90 quarter units of all coursework. Also required are an upper-division statistics course, one or more college calculus course(s), and at least one college-level programming course. An applicant might be conditionally admitted to the program with marginal deficiency in the above requirements.
Admission to Conditionally Classified Standing
An applicant might be conditionally admitted to the program with marginal deficiency in the above requirements. The individual admission notification will explain required terms and conditions for attaining Classified standing.
Requirements for Advancement to Candidacy
The university requirements for advancement to candidacy for the master's degree are outlined in the Graduate Policies and Procedures section of this catalog. Candidacy includes successful completion of the Graduation Writing Assessment Requirement (GWAR), described in this catalog. DATA 294 is a multidisciplinary seminar class that exposes students to multiple domains in data analytics and satisfies the Graduation Writing Assessment Requirement (GWAR) for this program. For graduate courses that meet the GWAR, refer to the GWAR Course List on the Graduate Studies website.
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.
MS - Data Analytics Graduation Requirements
This is an interdisciplinary program consisting of 10 courses with both in-person and online modes. As shown below, each of the 6 core, 2 elective, and 2 thesis or project courses is 3 semester units.
Culminating Experience (Plan A or Plan B)
All students must complete one of the following culminating experience options as part of their 30-unit program requirement.
Plan A (Thesis)
Students opting to complete a master's thesis will take the DATA 299A and DATA 299B as a two-course sequence. The student is responsible for securing the commitment of a full-time tenured or tenure-track faculty member who agrees to serve as the thesis committee chair. The student must also secure the commitments of two additional university faculty members, one of whom must be a full-time tenured or tenure-track faculty member, to serve as the student's thesis committee. The student must write a thesis proposal and have it approved by the thesis committee and pass the DATA 299A before enrolling in the DATA 299B. The thesis must meet university requirements as stipulated in this catalog and in the SJSU Master's Thesis and Doctoral Dissertation Guidelines (pdf). It will be written under the guidance of the candidate's thesis committee chair with the assistance of the thesis committee.
Plan B (Project)
The graduate project is a research or development effort performed by a team of students on a topic chosen by mutual agreement between an advisor and the team. The choice of project topic must also be approved by the instructor of DATA 298A. DATA 298A is the first part of the master's project in which students develop a comprehensive plan and preliminary design of a data analytics project. DATA 298B is the second part of the master's project course in which each students complete an in-depth written projects to achieve the program outcomes and satisfy the program culminating experience requirement.
Special Session Program Information
Programs offered through Special Session are operated by the College of Professional and Global Education (CPGE). Registration and enrollment in a Special Session course or program must use the special session application form and will follow special session fee and course schedules. Note that regular session students seeking to enroll simultaneously in a special session course or program will trigger a separate and additional set of fees. This may require an additional enrollment appointment from the Registrar and it may have implications for financial aid status or requirements. Please visit the CPGE website for more information.
|Graduation Writing Assessment Requirement|
|At SJSU, students must pass the Graduation Writing Assessment Requirement (GWAR). For information on the GWAR, please see http://info.sjsu.edu/gcw.html.|
|Requirements of the Masters||30|
|BUS 243. Database Management||3|
|CMPE 257. Machine Learning||3|
|DATA 220. Mathematical Methods for Data Analysis||3|
|DATA 294. Data Analytics Seminar||GWAR||3|
|INFO 215. Information Visualization||3|
|Complete one course from:|
|BUS 235C. Data Mining||3|
|CMPE 255. Data Mining||3|
|Six units 200-level elective courses selected in consultation with the graduate advisor|
|Complete one plan from:|
|Plan A (Thesis)||6|
|DATA 299A. Data Analytics Masters Thesis I||3|
|DATA 299B. Data Analytics Masters Thesis II||3|
|Plan B (Project)||6|
|DATA 298A. Data Analytics Masters Project I||3|
|DATA 298B. Data Analytics Masters Project II||3|
Upon completion of the degree requirements, the student must have achieved minimum candidacy and SJSU Cumulative grade point averages of 3.0 in order to graduate.