UCLA Luskin students seeking to verify the quantitative classes they have taken outside of core requirements may earn this certificate as a signal to employers of their training in quantitative analysis. Although qualitative data analytics is also valuable, this certificate is designed for students focusing on techniques and resources related to quantitative data analytics.


AVAILABILITY: The Certificate in Data Analytics has been available to UCLA Luskin students since fall 2021.

REQUIREMENTS.  To receive a certificate, students must complete three courses and produce a competency product.

  • Courses are grouped thematically, and students can take courses from any group, with the exception that all students must take one course from the Technology Policy track. Only one course from the Technology Policy and Ethics track will count towards completion of the certificate.
  • Students are required to produce a competency product to receive the certificate, though the product does not have to be in addition to what a student’s home department requires. To receive credit as a competency product, the work must involve the use of code and demonstrate advanced skills such as, but not limited to, geospatial analysis, machine learning, natural language processing, network analysis, regression analysis, structural equation modeling, or visualization.  (Geospatial analysis is possible using R, Python, and other programming languages.  A product using ArcGIS without scripts will not count as a competency product).  Code must also be provided that produces the output in the competency product.  Example opportunities to complete a competency product include class projects, a quantitative part of a capstone project, or work from an internship or job.  The product cannot be produced as part of a course that counts towards the certificate unless the requirements for the certificate have already been fulfilled.

The competency product will be submitted to the committee member of the student’s department and can be submitted on a rolling basis. Because it is possible that a competency product will not be approved, students are strongly encouraged to receive approval well in advance of graduation.  If a competency product is presented and deemed not sufficient and there is not time for the student to complete a different one, the certificate will not be awarded. The student is responsible for showing that this product demonstrates quantitative analytical skills beyond what is expected from core classes.

SCOPE: For a course not in the Technology Policy track to count toward the certificate, students must utilize software tools that are not part of the Microsoft or Google productivity suites (or similar suites from competitors such as LibreOffice). The software tool must include quantitative analysis available via programming languages such as R or Python or through advanced software such as Stata or ArcGIS.

The quantitative analysis of qualitative data is allowed, but qualitative evaluation on its own is not.

Such a class must be offered outside of the core courses taken by all students pursuing a degree in Public Policy, Social Welfare or Urban Planning at UCLA Luskin. The course can be part of another UCLA department’s core curriculum if the enrollee takes the class as an elective and a Data Analytics committee member approves it toward the certificate in advance.


Students must choose at least one course from the Technology Policy and Ethics track, and at least two other courses, which may be derived from any of the other tracks. Only one course from the Technology Policy and Ethics track will count towards completion of the certificate. A working list of subject areas and example courses that count for credit are presented below, with the expectation that additional courses will be identified and approved by certificate administrators in consultation with individual students once the program has formally launched. Inclusion of courses from outside the Luskin School are also subject to approval by the instructor and department.

Spatial Analysis
Courses focusing on Geographic Information Systems (GIS) and mapping

    • PUB PLC M221/URBN PL M253: Travel Behavior Analysis
    • PUB PLC 224A: Introduction to Geographic Information Systems (GIS); equivalent of URBN PL 206A
    • PUB PLC 224B: Advanced Geographic Information Systems (GIS); equivalent of URBN PL 206B
    • URBN PL 221: Introduction to Geographic Information Systems (GIS) and Spatial Data Science; equivalent of PUB PLC 224A
    • URBN PL 206B: Advanced Geographic Information Systems (GIS) Spatial Data Analysis; equivalent of PUB PLC 224B
    • URBN PL M215/GEOG M205*/STATS M222*: Spatial Statistics

Data Science
Programming courses using R

    • BIOSTAT 203A*: Introduction to Data Management and Statistical Computing
    • PUB PLC M276A/EDUC M260A*: Introduction to Programming and Data Management
    • PUB PLC M276B/EDUC M260B*: Fundamentals of Programming
    • PUB PLC 291A: Introduction to Data Science Using R
    • URBN PL 229: Urban Data Science

Advanced Methods
Statistics courses with a strong programming component

    • PUB PLC C277: Network Science Using R

Program Evaluation
Tools and survey methods courses with a technological focus

    • PUB PLC 272: Tools for Causal Inference
    • PUB PLC 273: Survey Analysis
    • SOC WLF 286B: Advanced Research Methods

Technology Policy and Ethics
Courses that focus on data, technology and its use in policymaking and governing

    • PUB PLC 274: Social Media and Public Policy
    • PUB PLC C275: Advanced Technology: Public Policy, Regulation, and Law
    • PUB PLC 291A: Digital Government
    • LAW 386*: Digital Technologies and the Constitution
    • LAW 483*: Privacy, Data, and Technology
    • LAW 511*: Social Media and the Future of Democracy
    • MGMT 298D*: Technology & Society: A Dynamic Relationship and the Changing Role of Leaders

* Offered outside of UCLA Luskin.

If you would like to register for the certificate, please complete this form.


Zachary Steinert-Threlkeld
Associate Professor of Public Policy

Adam Millard-Ball
Professor of Urban Planning