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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.

OVERVIEW

AVAILABILITY: The Certificate in Data Analytics is available to UCLA Luskin students as of fall 2021, with the first certificates expected to be awarded in June 2022.

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.
  • 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.  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.

COURSEWORK

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. 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 GIS and mapping

    • UP 206A – Introduction to Graphical Information Systems and Spatial Data Science
      • PP 224A – Introduction to GIS.  The equivalent in Public Policy.
    • UP 206B – Advanced Geographic Information Systems
      • PP 224B – Advanced GIS.  The equivalent in Public Policy.
    • M 253 – Travel Behavior Analysis
    • Geography M205*, Statistics M222*

Data Science
Programming courses using R

    • UP 229 – Urban Data Science.
    • PP 291A – Introduction to Data Science Using R.
    • EDUC 260A* – Introduction to Programming & Data Management Using R
    • EDUC 260B* – Introduction to Programming & Data Management Using R
    • BIOSTAT 203A* – Introduction to Data Management and Statistical Consulting

Advanced Methods
Statistics courses with a strong programming component

    • PP 291A – Arguing with Data: Introduction to Descriptive Data Analysis
    • PP 291A – Network Science Using R

Program Evaluation
Tools and survey methods courses with a technological focus

    • PP 291A – Tools for Causal Inference
    • PP 291A – Survey Methods
    • SW 286B – Advanced Research Methods

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

    • PP 291A – The Digital Public Sector: Principles of Governing with Data and Technology (This class is the same as PP291A – Digital Government)
    • PP 291A – Advanced Technology: Public Policy, Regulation, and Law
    • PP 291A – Social Media and Public Policy
    • Law 386* – Digital Technologies and the Constitution
    • Law 483* – Privacy, Data, and Technology

* Offered outside of UCLA Luskin.

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

CONTACT

Zachary Steinert-Threlkeld
Associate Professor of Public Policy and Public Policy
zst@luskin.ucla.edu

V. Kelly Turner
Associate Professor of Urban Planning and Geography
vkturner@g.ucla.edu