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The UCLA Master of Engineering (MEng) in Data Science Engineering is a professionally oriented, STEM-designated graduate program designed to prepare students for leadership and technical roles in the fast-evolving field of data science. Offered by the UCLA Samueli School of Engineering, the program blends advanced coursework in data engineering, machine learning, and AI with training in engineering leadership, innovation, and entrepreneurship.
Ideal for technically trained students and professionals seeking to gain expertise in both data science and management, the program is housed in the vibrant tech ecosystem of Los Angeles, offering strong connections to the AI, media, healthcare, and tech sectors.
Program Format & Duration
Full-time, on-campus program
Duration: 1 year (3 quarters)
STEM-designated (eligible for up to 3 years OPT for international students)
Culminates in a capstone project, not a thesis
Entry: Fall intake only
Core Curriculum Components
The MEng curriculum is divided into three components: Technical Depth, Leadership & Business Skills, and a Capstone Project.
Technical Courses (Sample Topics)
Data Structures and Algorithms
Machine Learning for Data Science
Data Mining and Predictive Analytics
Statistical Inference and Modeling
Database Systems and Big Data Infrastructure
Artificial Intelligence Applications
Cloud Computing and Data Pipelines
Leadership & Management Courses
Offered through UCLA’s Engineering Management curriculum:
Engineering Project Management
Innovation and Entrepreneurship
Financial Decision-Making for Engineers
Organizational Behavior in Tech Teams
Technology Strategy and Business Model Innovation
Capstone Project
Team-based, real-world project sponsored by industry partners or UCLA research labs
Students work on end-to-end data science challenges, such as:
Predictive modeling for customer behavior
AI-driven risk analysis in finance
Data engineering for streaming media platforms
Health analytics using medical imaging or sensor data
The MEng program emphasizes applied learning, preparing students to immediately contribute in industry settings.
Capstone Highlights
Students work in interdisciplinary teams, integrating technical and leadership skills
Projects are supervised by both faculty advisors and industry mentors
Culminates in a final presentation and technical report
Industry Integration
Access to UCLA’s strong industry connections in the LA tech corridor
Frequent industry panels, guest speakers, and networking events
Exposure to startups, Fortune 500 companies, and public-sector innovation labs
Professional Development
Career workshops, technical interview prep, and resume reviews
Opportunities to participate in data science competitions and hackathons
Support for internship placements during or after the program (optional)
Graduates of UCLA’s MEng in Data Science Engineering are well-prepared for technical leadership roles in data-driven industries.
Career Outcomes
Common job roles include:
Data Scientist / Data Analyst
Machine Learning Engineer
Data Engineer / Platform Engineer
AI Product Manager
Business Intelligence Developer
Analytics Consultant
Top Employers
UCLA alumni are placed at:
Google, Meta, Amazon, Microsoft
Netflix, Hulu, Snap Inc.
Amgen, Kaiser Permanente (health analytics)
SpaceX, Northrop Grumman
Startups and consulting firms in AI, fintech, and edtech
Further Study
Graduates may also pursue:
PhDs in Data Science, Computer Science, or Engineering
MBA programs with tech or analytics focus
Certificates in niche areas like deep learning or cloud systems
Bachelor’s Degree: Hold a bachelor’s degree in an engineering, computer science, mathematics, physics, chemistry, or equivalent field, from an ABET-accredited (or recognized international) institution.GPA: Have a minimum GPA of 3.0 in your last two years of undergraduate coursework (waivers for slightly lower GPAs considered).Transcripts: Upload unofficial transcripts at application and provide official versions (with certified English translations if necessary) upon admission.Letters of Recommendation: Submit three letters—at least two academic; after three years from graduation, professional references may substitute. GRE: Not required for 2025–26 admission; GRE scores will not impact your evaluation. English Proficiency: International applicants must submit TOEFL (iBT ≥ 87), IELTS (≥ 7.0), or equivalent unless their degree was in English.Resume/CV: Provide a current résumé or CV detailing your technical experience and achievements.Statement of Purpose: Submit up to two essays (Statement of Purpose and Personal Statement), each up to 500 words. Prerequisite Background: Demonstrate proficiency in programming (especially Python), mathematics, and statistics through your academic or professional experience.Application Fee: Pay a non-refundable fee—$135 for U.S. citizens/residents, $155 for international (fee-waivers available). Deadlines & Format: Apply by December 1, 2025 (rolling review); program starts fall, full-time, one-year on-campus.Three-Year Bachelor’s Degrees: Applicants must hold a bachelor’s degree in engineering, computer science, mathematics, physics, chemistry, or equivalent from an accredited institution, and international three-year degrees are assessed individually under Graduate Division standards WES Evaluation: UCLA does not accept WES or other credential evaluations in place of official transcripts, requiring sealed institutional transcripts submitted directly from the awarding institution Data AnalystData ScientistBusiness AnalystStatisticianStatistical ProgrammerSAS ProgrammerMachine Learning EngineerDeep Learning EngineerAI ResearcherData EngineerBI DeveloperData ArchitectAnalytics ConsultantAdvisory ConsultantQuantitative AnalystRisk AnalystOperations AnalystMarketing AnalystResearch ScientistInsights AnalystForecasting AnalystHealthcare Data AnalystFinancial Data AnalystProduct Analyst
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