University of California, Los Angeles
Master of Engineering - Autonomous Systems
Last reviewed June 2026 by the AI Graduate editorial team. Program data is compiled and verified from official university sources β see our methodology.
How this program compares
At an estimated $52.9K in total tuition, the Master of Engineering - Autonomous Systems sits about 25% above the $42.4K average for AI master's programs in our database β placing it in the 72nd percentile on cost among the 531 we track at this level.
Admission Snapshot
Typical admitted student: A bachelor's degree in engineering, computer science, or a related field with a minimum GPA of 3.0 is required, along with relevant coursework in controls, programming, and mathematics. GRE scores are often optional, and prior experience in robotics or AI is preferred.
About This Program
This professional one-year program integrates expertise from multiple engineering disciplines to train leaders in the design and management of reliable, safe, and secure autonomous robotic devices. Coursework concentrates on Computer Vision and Machine Learning. Most students complete it in about 1 year.
Estimated total tuition is $52.9K, above the $42.4K average for AI master's programs in our database and in the 72nd percentile on cost at this level. Applicants should weigh that premium against the program's outcomes and brand.
Lead as Robotics Engineer in Autonomous Vehicles with machine learning expertise Graduates frequently move into roles such as Robotics Engineer, with reported salaries around $125,000.
Career Outcomes
Lead as Robotics Engineer in Autonomous Vehicles with machine learning expertise
- 1. Autonomous Systems Engineer
- 2. Robotics Software Developer
- 3. Control Systems Engineer
- 4. AI Perception Specialist
What You'll Learn
- Develop perception algorithms for real-time environmental sensing in autonomous vehicles.
- Design motion planning and decision-making systems for safe robotic navigation.
- Implement feedback control strategies for dynamic cyber-physical systems.
- Apply machine learning techniques to optimize autonomous system performance.
Curriculum Highlights
The curriculum features technical core courses in dynamic systems and control, professional development electives, and an industry-sponsored capstone project focused on real-world engineering challenges.
Top Employers
Top employers include Waymo, Tesla, Boston Dynamics, and aerospace firms like Northrop Grumman.
Admissions
A bachelor's degree in engineering, computer science, or a related field with a minimum GPA of 3.0 is required, along with relevant coursework in controls, programming, and mathematics. GRE scores are often optional, and prior experience in robotics or AI is preferred.
Application Materials
- Statement of Purpose: Required
- Letters of Recommendation: 2β3
- Resume: Required
- Transcripts: Official transcripts required
Academic Requirements
- Degree Required: Bachelor's degree
- GRE/GMAT: Optional
- TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)
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