Masters in Robotics and Embedded Software (EECS)

Class Profile

Class Size

25

Average Age

28

Average Work Experience

2 Years

Diversity

Others:

10%

United States:

35%

International:

25%

California:

30%

Career Outcomes

Median Earnings After Graduation

$1,10,000 / year

Top recruiters

Accenture

Deloitte

Google

Amazon

Microsoft

Apple

Facebook

Dell

Spotify

Tesla

Meta

Wipro

Fees and Funding

Tuition Fees

$35,775 / year

Overall Cost

$50,775 / year

FAQs

• What are the career outcomes for graduates?
  
  Graduates enter careers in robotics, autonomous vehicles, embedded software, aerospace, AI systems, IoT, defense, and advanced manufacturing. Employers include tech firms, robotics startups, research labs, and government agencies. Many MS graduates also continue toward a PhD in EECS or Robotics.
• What kinds of research or projects can students work on?
  
  Students may engage in projects through labs such as Berkeley Artificial Intelligence Research (BAIR), Berkeley Robotics and Intelligent Machines Lab, or the Hybrid Systems Lab. Topics include autonomous vehicles, UAVs, embedded AI, cyber-physical systems, computer vision, and robotic learning.
• What academic background is required for admission?
  
  Applicants should hold a bachelor’s degree in electrical engineering, computer science, robotics, mechanical engineering, or a related field. Strong preparation in programming (C/C++/Python), algorithms, control theory, embedded systems, and linear algebra is expected.
• Is this program offered as an MS or MEng degree?
  
  Robotics and Embedded Software can be pursued as part of either the Master of Science (MS, research-based) or the Master of Engineering (MEng, professional, coursework-based) programs within EECS. The MS track emphasizes research and thesis work, while the MEng track is designed for industry-focused career preparation.
• What is the focus of the Robotics and Embedded Software program at UC Berkeley?
  
  The program combines robotics, embedded systems, and software engineering under the Department of Electrical Engineering and Computer Sciences (EECS). It emphasizes autonomous systems, control, sensing, machine learning, embedded programming, and real-time computation for robotics and intelligent devices.