UCLA Data Science Engineering Minor Guide For 2026

UCLA Data Science Engineering Minor Guide For 2026

Minor in Education Studies - UCLA School of Education & Information Studies

Navigating the intersection of quantitative analysis, computational modeling, and domain expertise requires a structured academic path, making the Data Science Engineering (DSE) minor at UCLA one of the most sought-after interdisciplinary credentials for undergraduates in 2026. Administered through the UCLA Henry Samueli School of Engineering and Applied Science, this minor equips students from both engineering and non-engineering majors with the programmatic, statistical, and algorithmic toolkit required to extract actionable insights from massive datasets. Because "DSE minor UCLA" can occasionally be confused with general data analytics certificates or pure statistics tracks, this guide focuses entirely on the official Samueli School engineering minor in Data Science Engineering, outlining curriculum prerequisites, declaration procedures, and strategic course selection for the 2026 academic year.


Academic Prerequisites and Eligibility Requirements

Securing admission into the UCLA Data Science Engineering minor demands careful long-term planning, particularly regarding foundational lower-division coursework in mathematics and programming. The Samueli School maintains rigorous academic standards to ensure that enrolled students possess the quantitative maturity required for upper-division machine learning and database systems coursework.



  • Minimum Grade Point Average: Applicants must maintain a cumulative GPA of 3.0 or higher across all coursework completed at UCLA and specifically within the prerequisite sequence.
  • Calculus Sequence: Completion of the standard engineering calculus series—typically Mathematics 31A, 31B, 32A, 32B, and 33A (or equivalent linear algebra and differential equations courses)—with grades of C or better.
  • Programming Proficiency: Demonstrated competency in foundational programming, usually satisfied through Computer Science 31 (Introduction to Computer Science) or approved equivalents focusing on object-oriented programming paradigms in languages like C++ or Python.
  • Standing Restrictions: Students must apply for the minor before completing 135 units (junior standing cutoff) to ensure they can complete all upper-division requirements within their normative time to degree.

Important Advisor Note: Declaring the DSE minor does not automatically grant priority enrollment (golden ticket status) into high-demand upper-division computer science electives. Students must coordinate closely with both their major departmental counselor and the Samueli undergraduate student affairs office to plan alternative course pathways.

Core Curriculum and Upper-Division Course Breakdown

The 2026 curriculum structure of the DSE minor bridges core computational theory with practical data manipulation frameworks. Students must navigate a structured sequence of mandatory foundational classes followed by specialized technical electives. The program emphasizes relational database architecture, statistical inference, and scalable machine learning algorithms.



Requirement Category Required Courses / Options Units Focus Area
Lower-Division Prep COM SCI 31, MATH 32A, MATH 33A 12-16 Syntax, Matrices, Multivariable Calculus
Core Computing COM SCI 32, COM SCI M146 (Machine Learning) 8 Data Structures, Algorithms, Predictive Modeling
Data Systems & Stats COM SCI 143 (Data Management), STATS 100A 8 SQL, Relational Schemas, Probability Theory
Technical Electives Two approved upper-division CS, ECE, or STATS courses 8 Deep Learning, NLP, Data Privacy, Visualization

Beyond standard lectures, the program encourages engagement with practical data engineering problems, requiring students to understand how to clean, store, and process unstructured information at scale. Elective options are updated annually to reflect industry shifts, incorporating modern distributed computing frameworks and ethical artificial intelligence governance standards.


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Strategic Comparison: DSE Minor vs. Statistics Major and Data Theory Major

Choosing the right quantitative credential at UCLA requires balancing engineering computational depth with statistical theory. Many undergraduates weigh the Samueli DSE minor against standalone majors or alternative minors.



Program Feature DSE Minor (Samueli Engineering) Statistics Major (L&S) Data Theory Major (Math/Stats)
Primary Focus Systems, algorithms, and database engineering Applied statistics, inference, and modeling Mathematical foundations of data science
Programming Intensity High (C++, Python, SQL, distributed frameworks) Moderate (R, Python, SAS) High (Python, R, mathematical proof software)
Target Audience Engineering and physical science majors Social sciences, life sciences, and business Pure mathematics and theoretical computation
Flexibility Integrates into non-CS majors as a supplementary badge Requires full major declaration Requires rigorous upper-division math tracking

For students already pursuing demanding engineering disciplines such as Mechanical, Electrical, or Bioengineering, the DSE minor provides the exact computational badge needed to pivot into quantitative tech roles without changing their primary major.

Step-by-Step Guide to Declaring and Completing the Minor

Navigating the administrative lifecycle of the DSE minor requires adherence to strict departmental deadlines and proactive engagement with the Samueli School counseling portal.



  1. Verify Unit Thresholds: Confirm that your total earned units at UCLA are below the 135-unit ceiling. Exceeding this limit without an approved petition will result in immediate denial of the minor application.
  2. Complete Prerequisites: Finish all required lower-division math and introductory programming courses, ensuring all grades are posted on your DARs (Degree Audit Report System).
  3. Submit the Official Petition: Access the undergraduate student affairs portal on the Samueli School website during designated application filing periods (typically open during the first three weeks of Fall, Winter, and Spring quarters).
  4. Draft a Graduation Plan: Construct a realistic quarter-by-quarter course map showing that all remaining upper-division minor classes can be completed alongside major requirements without exceeding your college unit cap.
  5. Meet with a Counselor: Schedule an appointment with a Samueli engineering counselor to review your study list, secure official departmental sign-off, and update your official university record.

Frequently Asked Questions



Can non-engineering majors (such as Economics or Cognitive Science) apply for the DSE minor?

Yes, non-engineering students are eligible to apply, provided they meet all lower-division mathematics and programming prerequisites and maintain the required minimum GPA. However, competition for space can be high, making early prerequisite completion essential.



Does the DSE minor guarantee enrollment in impacted Computer Science classes?

No, minor students do not receive priority enrollment (Phase 1) for impacted Computer Science and Engineering courses, meaning you may need to wait until pass 2 or pass 3 to secure seats in high-demand electives.



How many upper-division units from the minor can overlap with my major?

UCLA regulations generally permit a maximum of two upper-division courses (or eight units) to overlap between a student's major requirements and an official minor program.



Are there practical capstone or project opportunities within the DSE minor?

While a standalone capstone is not universally mandatory for the minor, many of the approved upper-division technical electives incorporate semester-long collaborative projects utilizing real-world datasets.



What career paths are most accessible for graduates with a UCLA DSE minor?

Graduates frequently transition into roles such as data engineer, junior machine learning developer, quantitative analyst, and software developer within tech, finance, healthcare, and consulting sectors.

Optimizing Your Undergraduate Journey in Data Science

Succeeding in the UCLA Data Science Engineering minor demands a blend of rigorous technical preparation and strategic course mapping. By combining foundational engineering principles with modern computational frameworks, you position yourself at the forefront of quantitative innovation. Review your academic standing, plan your prerequisite trajectory early, and leverage UCLA's extensive research centers and recruitment pipelines to maximize the value of your credential.


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