Electrical & Computer Engineering Department

Master of Science in 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), Networking and 5G wireless communications, and embedded systems are changing many aspects of daily life, including driving, entertainment, communication, health care, and virtual and robotic assistants. These changes are creating many new engineering jobs in the fields of AI applications, AI chip design, smart edge-device design, IoT system design, and intelligent system design.

The Master of Science in Computer Engineering (MSCE) degree program will focus on the overlap of electrical engineering and computer science. MSCE students will learn to design embedded systems that power the IoT system and study the design techniques that are used in wearable vital sign monitoring devices such as Apple watch. The MSCE 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

ECE 557 AI & Machine Learning
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 Course

» CEN 551 Computer Architecture
» CEN 556 Distributed Computing Systems
» CEN 540 Network Security Techniques
» CEN 542 Computer Vision and Image Processing
» CEN 548 Computer Network Systems
» CEN 581 Principle of Internet of Things
» ECE 505 Machine Learning Fundamentals
» ECE 510 Algorithms and Data Analysis
» ECE 610 Algorithm on a Chip
» ECE 646 IoT System Design
» ECE 688 Special Topics in Computer Engineering
» ECE 689 Independent Study
» ECE 758 Advanced IoT System Design
» EEN 520 ASIC Design I
» EEN 525 ASIC Design II
» EEN 629 System on a Chip (SOC) Design
» EEN 766 Advanced Communication Systems
» 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.



should apply

As an ITU computer engineering student, you can:

  • Concentrate on some of the most cutting-edge technologies and their implementations in system design
  • Learn from instructors who come from industry-leading companies like ARM, Fujitsu, and Intel, and receive insider insight into the latest trends
  • Conduct laboratory research in such areas as: Artificial Intelligence, Internet of Things, Bioelectronics, System-on-chip, and more
  • Be part of a STEM program designed to teach students the skills required to thrive in Silicon Valleys ever-evolving tech sector

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.