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The 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.

 

 

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The Master of Science in Electrical and Computer Engineering (MSECE) degree program will focus on the overlap of electrical engineering and computer engineering. MSECE students will study and also learn to design integrated hardware and software systems, using computer architectures, computing algorithms, IC design, distributed systems, intelligent system design and applications.

 

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Applicants must have completed a minimum of 45 semester hours of college-level engineering topics and a minimum of 30 semester hours of college-level mathematics and basic science courses. Students accepted to the MSCE and MSEE programs will work with their assigned faculty advisor to develop an individual study plan and ensure that they fulfill ABET Graduate Student Outcomes (GSO) upon graduation.

Master of Science in Electrical and Computer Engineering

Curriculum, Program Structure, and Admissions Requirements

Program Requirements

In addition to ITU’s university-wide admission requirements, applicants to the MSECE program must have completed a minimum of 45 semester hours of college-level engineering topics, and a minimum of 30 semester hours of college-level mathematics and basic science courses.

Faculty will assess each student after admission, and will supervise students to develop individualized study plans with specific goals.

The MSECE program requires 36 credit hours for graduation consisting of at least 15 hours of required credits and 21 hours of elective credits, including a minimum of 6 elective credit hours in field-relevant courses.

A minimum of 30 credit hours must be earned through course work. If a student is eligible to take more than 6 credit hours of Internship, and chooses to do so, the total number of credit hours required for graduation will increase accordingly.

Program Structure

Required Courses
  • 4 Core Courses: 12 Credit Hours
  • 1 Capstone or Thesis Project: 3 Credit Hours
  • Internship: 1 Credit Hour

 

Elective Courses
  • Field Relevant Courses: 9 credit hours
  • 1 Cross Disciplinary course from MBA, EM or DA: 3 credit hours
  • Transfer Credits: Up to 9 credit hours from a graduate program of a regionally accredited school with department chair’s approval
  • Any course in CE, EE, CS, SE or Math


36 Total Credit Hours

GRADE POINT AVERAGE (GPA):

A minimum 3.0 cumulative GPA is required for granting of the Master’s degree.

Required Core Courses

Select four from the following list:

  • ECE 500 Electrical and Computer Engineering
  • ECE 510 Algorithms and Data Analysis
  • CEN 551 Computer Architecture
  • CEN 556 Distributed Computing Systems
  • EEN 511 Integrated Circuit Design
  • Digital Signal Processing and System Analysis


CAPSTONE COURSE

Select one from the following list:

  • ECE 646 Capstone Course 1 – IoT System Design
  • EEN 627 Capstone Course 2 – Chip Design to Silicon
  • ECE 655 Capstone Course 3 – Deep Learning Engineering Projects


ELECTIVE COURSES

Electrical and Computer Engineering Field Relevant: minimum of 3 courses:

  • AMS 512 Applied Mathematics Methods
  • AMS 540 Discrete Mathematics
  • AMS 552 Probability, Statistics and Reliability for Engineers
  • AMS 722 Advanced Applied Mathematics Methods
  • AMS 750 Abstract Algebra
  • AMS 760 Advanced Optimization Techniques
  • CEN 508 Scientific Computing
  • CEN 520 Artificial Intelligence Application Development
  • 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 521 AI Design Using FPGA
  • 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 Devices and Systems
  • EEN 635 Introduction to MEMS Design
  • EEN 671 Wireless Communication Systems
  • EEN 688 Special Topics
  • EEN 689 Independent Study
  • EEN 715 Advanced Computer Architecture
  • EEN 717 Advanced Integrated Circuit Design
  • EEN 733 Advanced Computing Technology
  • 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


OTHER ELECTIVE COURSES

Any course in Math, MSEE, MSCE, MSSE or MSCS can be accepted as an elective course

One cross-disciplinary course (MBA, EM or DA) can be accepted as an elective course


INTERNSHIP

  • CFL 591 Integrating Academic & Internship Learning
  • INT 593 Part-time/Full-time Internship

Admission Requirements

  • Bachelor’s degree with a minimum GPA of 2.75, or a Master’s degree with a minimum GPA of 3.0.
  • Test of English as a Foreign Language (TOEFL) examination: score of 72 or better for the internet-based test (iBT). All applicants whose native language is not English and who did not receive either a bachelor’s or graduate degree from an English-speaking institution must take an English proficiency test.*
  • International English Language Testing System (IELTS) examination: band score of 6.0 or better for the academic module. Demonstrated commitment to contribute to and complete the program

*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.

Master of Science in Electrical and Computer Engineering

Program Learning Outcomes

Program Learning Outcomes

The Program Learning Outcomes (PLO) define the educational outcomes of the MSECE degree program:

  • PLO 1: Fundamentals: (ILO 5) Explain current and emerging technologies in computer architecture, algorithms, and hardware and software design

  • PLO 2: Engineering Ability: (ILO 1) Appraise integrated electrical and computer engineering problems using contemporary techniques

  • PLO 3: Research Ability: (ILO 6) Conduct independent research to solve challenges in electrical or computer engineering 

  • PLO 4: Career Responsibility: (ILO 7) Apply professional ethics in the definition, planning, and execution of engineering projects

  • PLO 5: Critical Thinking:  ILO 2) Analyze engineering challenges to make evidence-based choices among various paradigms

  • PLO 6: Communication Skills: (ILO 3) Present technical issues clearly in oral and written communications

  • PLO 7: Team Work: (ILO 4) Support team effort through collaboration to achieve project goals

 

Master of Science in Electrical and Computer Engineering

ABET Outcomes

ABET Outcomes

The ABET Graduate Student Outcomes (GSO) further describe what MSECE students are expected to know and be able to do by the time of graduation.  The GSO represent skills, knowledge, and abilities a student should possess as a condition for entry into the profession upon graduation.

  • GSO 2: An ability to conduct graduate-level engineering design and research

  • GSO 3: An ability to communicate professionally and work effectively in a team environment

The ABET Program Educational Objectives (PEO) describe what graduates are expected to attain within the first few years after graduation.

  • PEO 1: Graduates of the MSECE program solve computer and electrical engineering problems for high-tech industries, mainly in Silicon Valley

  • PEO 2: Graduates perform engineering design, research and product development

  • PEO 3: Graduates are effective team members or leaders