Electrical & Computer Engineering Department

Master of Science in Electrical and Computer Engineering

As technology advances ever more rapidly, the computer industry and society as a whole need professionals who possess a combination of electronic hardware and computer software skills. These skills should be developed in the context of modern systems to make them more practical and useful. 

Artificial Intelligence (AI) innovations and applications, the Internet of Things (IoT), and 5G wireless communications are changing many aspects of daily life, including driving, enter-tainment, communication, health care, and virtual and robotic assistants. These changes are creating many new engineering jobs in the fields of AI chip design, smart edge-device design, IoT system design, and intelligent system design.

The department’s chip design environment conforms to industry standards and gives you the practical training you need for your career. Advanced design and computation projects will help you hone your hands-on techniques and skills. You’ll also develop innovation and entrepreneurship-focused thinking through cutting-edge research. The MSEE students can take the AI concentration as an option. The AI concentration is designed based on the latest trends in the industry in developing Deep Learning and reinforcement learning algorithms and deploying them on the edge devices.


Our 39 credit hour curriculum is completed in 16 months. The 39 credit hours are composed of core courses, electives, cross disciplinary electives, capstone or thesis, and an internship.

Program Structure

Required Courses

  • 3 Core Courses (9 credit hours)
  • Elective Courses (15 credit hours)
  • Capstone course – Project or Thesis (3 credit hours)
  • Internship know more
  • Nugget courses (up to 3 credit hours)
    • ITU Presents (1 credit hour)
    • ITU Nuggets (2 credit hours)

Core Courses:

CEN 548 Computer Network Systems
ECE 502 Advanced Python Applications
EEN 541 Digital Signal Processing and System Analysis

Elective Courses: 15 Credit Hours

  • Field Relevant Courses in the ECE Department.
  • Internship: know more
  • With approval from the ECE Department any course from
    • Department of Business Administration
    • Department of Computer Science
    • Department of Digital Arts
    • Department of Electrical and Computer Engineering
  • Transfer Credits: A maximum of 9 credit hours can be transferred from a regionally accredited graduate school with department chair’s approval.

Selected List of Elective Courses (see the course catalog for full list)

» ECE 504 Operating system design and implementation
» ECE 510 Algorithms and Data Analysis
» CEN 551 Computer Architecture
» CEN 540 Network Security Techniques
» CEN 542 Computer Vision and Image Processing
» CEN 548 Computer Network Systems
» CEN 556 Distributed Computing Systems
» CEN 581 Principle of Internet of Things
» EEN 513 Microprocessor Design
» EEN 520 ASIC Design I
» EEN 525 ASIC Design II
» EEN 616 Mixed Signal IC Design
» EEN 618 Analog and RF IC Design
» EEN 629 System On a Chip (SOC) Design
» EEN 630 Quantum Computing and Systems136
» EEN 635 Introduction to MEMS Design
» ECE 646 IoT System Design
» EEN 671 Wireless Communication Systems
» EEN 717 Advanced Integrated Circuit Design
» EEN 736 Advanced MEMS Design
» EEN 739 Bioelectronics and Bioengineering
» EEN 749 Advanced Digital Signal Processing
» EEN 753 Advanced Machine Learning Engineering
» EEN 758 Advanced System Design
» EEN 774 Advanced Wireless Communications
» INT 593 Part-time/Full-time Internship

Admission Requirements

  • Click here for Admission Requirements.

*U.S. citizens or U.S. Permanent Residents who have earned an undergraduate or graduate degree from a regionally accredited institution in the U.S. are waived from this requirement.

*Who has 2+ years of work experience in the United States are waived from this requirement.




As an ITU electrical engineering student, you can:

  • Concentrate on some of the most exciting technologies in the world today, such as VLSI design, analog, signal processing and communication, and system design
  • Implement design specifications and solve engineering problems through analysis, experimentation, and verification of ideas
  • Conduct research in ITUS laboratory facilities in areas like artificial intelligence, green energy, bioelectronics, and more
  • Get hands-on design and research experience utilizing EDA tools from Synopsys, Cadence, Mentor, and free chip design tape-out and chip packaging through MOSIS

What You Will Learn

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.

Learning Outcomes


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.

Support team effort through collaboration to achieve project goals.