Requirements for Graduation

Graduate in regalia

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 - Applied Data Intelligence Graduation Requirements

This program consists of 30 semester units of 200-level courses with a cumulative GPA of 3.0 or better. The program has developed two specializations: Specialization in Analytics Technologies and Specialization in Data Engineering. These specializations will be offered according to industry trends, student demands and resource availability. 

Graduation Writing Assessment Requirement

At SJSU, students must pass the Graduation Writing Assessment Requirement (GWAR).

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 of the Applied Data Science Department 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 of the Applied Data Science Department, 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 course before enrolling in DATA 299B. The thesis must meet university requirements as stipulated in this catalog and in the SJSU Master’s Thesis and Doctoral Dissertation Guidelines. 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 student completes an in-depth written project to achieve the program outcomes and satisfy the program’s culminating experience requirement.

Master’s Requirements (30 units)

Core Courses (15 units)

  • DATA 220 - Advanced Mathematical Methods for Data Intelligence 3 unit(s)
  • DATA 228 - Big Data Technologies and Applications for Data Intelligence 3 unit(s)
  • DATA 230 - Data Intelligence and Visualization 3 unit(s)
  • DATA 245 - Machine Learning Technologies 3 unit(s) (GWAR)
  • DATA 255 - Deep Learning Technologies 3 unit(s)

Elective Courses (9 units)

Complete three courses from one specialization:

Analytics Technologies

  • DATA 225 - Database Systems and Management for Data Intelligence 3 unit(s)
  • DATA 240 - Data Mining Techniques and Applications for Data Intelligence 3 unit(s)
  • DATA 265 - Large Language Model Applications 3 unit(s)

Data Engineering

  • DATA 226 - Data Warehouse and Pipeline Development 3 unit(s)
  • DATA 236 - Distributed Systems for Data Engineering 3 unit(s)
  • DATA 266 - Generative Models Applications 3 unit(s)

Culminating Experience (6 units)

Plan A (Thesis) (6 units)

  • DATA 299A - MSADI Thesis I 3 unit(s)
  • DATA 299B - MSADI Thesis II 3 unit(s)

Plan B (Project) (6 units)

  • DATA 298A - MSADI Project I 3 unit(s)
  • DATA 298B - MSADI Project II 3 unit(s)

Total Units Required (30 units)

Upon completion of the degree requirements, the student must have achieved minimum candidacy and SJSU Cumulative grade point averages of 3.000 in order to graduate.

For course inventory and descriptions please refer to the SJSU Catalog.