Electrical & Computer Engineering Department
Master of Science in Electrical Engineering
The Department of Electrical and Computer Engineering offers you the chance to work with industry-connected faculty on real-world projects through three research-oriented research projects: Master’s in Electrical Engineering, Master’s in Computer Engineering, and PhD in Electrical Engineering.
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.
Curriculum
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
Degree Requirements | Credits |
Core Courses | 9 |
Required MSCE Courses | 15 |
Required Capstone Courses | 3 |
Required ITU Presents | 1 |
Required Nugget Courses | 2 |
Internship | 1 |
Elective Courses | 8 |
Total | 39 |
Elective Courses:
- 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.
Core Courses
- CEN 548 Computer Network Systems
- ECE 502 Advanced Python Applications
- EEN 541 Digital Signal Processing and System Analysis
Capstone Courses
ECE 690 Capstone project or
ECE 698 Master Thesis
INTERNSHIP
INT 593 Internship – know more
ITU Presents
PRE-500 ITU Presents (1/3). *Students must take three ITU Presents courses for a total of 1 credit hour.
ITU Presents
Nuggets courses are typically coded between IDS 500 and IDS 599. For more details, consult the Chair Department.
Required Courses
Select a minimum of 5 Field Relevant courses from the MSEE Elective course list (refer to MSEE Elective Courses)
List of Elective Courses for MSCE
- 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
- ECE 505 Machine Learning Fundamentals
- ECE 510 Algorithms and Data Analysis
- ECE 610 Algorithm on a Chip
- 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
- ECE 630 Quantum computing and Systems
- 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 758 Advanced System Design
- EEN 774 Advanced Wireless Communications
- INT 593 Part-time/Full-time Internship

Who
should
apply
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
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.