The Masters of Science in Electrical Engineering (MSEE) degree program focuses on the following areas:
- Chip Design
- System Design
Integrated Circuit (IC) chips constantly bring revolutionary computing power to the world, empowering intelligent and automatic devices. AI chips implement artificial intelligence (AI) algorithms on IC chips to lead advanced technologies in engineering. System designs including embedded systems accomplish Internet of Things (IoT) from distributed systems to data collectors. Computer algorithms, networks, communications, scientific computing, software and coding skills are important knowledge to students for victorious in the field.
As an ITU computer engineering student, you can:
- Get hands-on design experience in embedded systems, integrated circuits, AI chips and applications, etc.
- Learn from instructors who come from industry leading companies like Intel and Google. They bring industry experience into the classroom and provide insight into the latest trends.
- Gain access to research conducted in state-of-the-art labs. Practice on research and design in current research developments.
- Be part of a STEM program designed to teach students the skills required to thrive in Silicon Valley’s ever-evolving tech sector.
Here are our program learning outcomes:
- Fundamentals: Explain current and emerging technologies in Chip Design or System Design in electrical engineering.
- Engineering Ability: Demonstrate an understanding of established and emerging engineering techniques, and problem-solving skills.
- Research Ability: Conduct independent research to solve challenges in electrical engineering.
- Career Responsibility: Apply professional ethics in the definition, planning, and execution of engineering projects.
- Critical Thinking: Analyze spectrum to make evidence-based choices between various engineering paradigms and alternative options.
- Communication Skills: resent technical issues clearly in oral and written communications.
- Teamwork: Support team effort through collaboration to achieve project goals.
Our 36 credit hour curriculum is completed in 16 months. The 36 credit hours are composed of core courses, electives, cross disciplinary electives, capstone or thesis, and an internship.
- Deep Learning in Engineering
- Distributed Computing
- Bioelectronics and Bioengineering
- Embedded System Design
- IC Design to Silicon
- 4 Core Courses: 12 Credit Hours
- Capstone or Thesis Project: 3 Credit Hours
- Internship: 1 Credit Hour
Elective Courses: 11 – 20 Credit Hours
- Minimum 6 Credit Hours in Computer Engineering
- Cross Disciplinary Electives: Up to 3 Credit Hours
- Transfer Credits: Up to 9 Credit Hours (Counts as Elective)
- Internship: 1 – 9 Credit Hours
36 Total Credit Hours
- EEN 500 Electrical Engineering (3)
- EEN 511 VLSI Design (3)
- EEN 541 Digital Signal Processing and System Analysis (3)
- CEN 510 Algorithms and Data Analysis (3)
Or CEN 508 Scientific Computing
Or CSC 580 Computer Algorithms
Capstone Course or Thesis
- EEN 646 Embedded System Design, or
- EEN 627 IC Design to Silicon, or
- CEN 643 Advanced Data and Image Processing, or
- EEN 698 Master Thesis I, or
- EEN 699 Master Thesis II