Cyber-Physical Systems Engineering

Curriculum

With the rapid pace of growth in Internet of Things (IoT) products and applications, there is a pressing need for engineers with unique skills in both hardware and software design.  Earning a Bachelor of Science in Cyber-Physical Systems Engineering (CPSE) from the Clark School of Engineering at the Unviersity of Maryland will train future engineers in both of these fields, with specializations in networks, cybersecurity, and machine learning.  

The cohort-based CPSE curriculum is designed to be completed in two years at the Biomedical Sciences and Engineering Building (BSE) at the Universities of Shady Grove campus in Rockville, MD. During their junior year,  students focus on foundational knowledge to prepare them for advanced-level topics in their senior year.  

CPSE Major Course Requirements

The CPSE major requires a total of 62 credits, with 60 credits completed prior to enrollment in the CPSE program. Students will take the program required courses in their junior and senior years, in addition to general elective coursework in the second semester of their senior year.  The specific elective course offerings will vary each spring semester. 

Program Educational Objectives (PEO's)

The program education objective of this program is to produce a well-trained workforce in the emerging technologies of internet of things. The Bachelor of Science in Cyber-Physical Systems Engineering will produce engineering graduates who:

  • Use their hardware and software engineering design training and problem-solving skills to contribute professionally in an industrial, research and applications environment;
  • Demonstrate initiative, leadership, teamwork, and continued professional development; 
  • Demonstrate understanding of the impact of their professional activities on society.

First Year CPSE Retention, Graduation Rate Average, and Current Student Enrollment

  • First year CPSE retention average over all cohorts: 77.8% (7/9 Students)
  • CPSE graduation rate average: 50% (2/4 Students)
  • Current Junior Cohort Enrollment: 5 Students
  • Current Senior Cohort Enrollment: 5 Students
  • 2023-2024 Total CPSE Enrollment : 10 Students

Student Learning Outcomes

  1. an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics.
  2. an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
  3. an ability to communicate effectively with a range of audiences.
  4. an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts.
  5. an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives.
  6. an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
  7. an ability to acquire and apply new knowledge as needed, using appropriate learning strategies.

TRACKS

HARDWARE TRACK

Course List
Course Title Credits
Required Courses  
ENEB455 Advanced FPGA System Design using Verilog for Embedded Systems 3
Elective Courses 9
Select three of the following:  

ENEB443

Hardware/Software Security for Embedded Systems  

ENEB451

Network Security  

ENEB452

Advanced Software for Connected Embedded Systems  

ENEB453

Web-Based Application Development  

ENEB456

Machine Learning Tools (Machine Learning Tools)  

ENEB457

Foundations of Databases for Web Applications  
Total Credits 12

COMPUTATIONAL TRACK

Course List
Course Title Credits
Required Courses  
ENEB456 Machine Learning Tools (Machine Learning Tools) 3
Elective Courses 9
Select three of the following:  

ENEB443

Hardware/Software Security for Embedded Systems  

ENEB451

Network Security  

ENEB452

Advanced Software for Connected Embedded Systems  

ENEB453

Web-Based Application Development (Web Based Application Development)  

ENEB455

Advanced FPGA System Design using Verilog for Embedded Systems  

ENEB457

Foundations of Databases for Web Applications  
Total Credits 12

SECURITY TRACK

Course List
Course Title Credits
Required Courses  
ENEB451 Network Security 3
Elective Courses 9
Select three of the following:  

ENEB443

Hardware/Software Security for Embedded Systems  

ENEB452

Advanced Software for Connected Embedded Systems  

ENEB453

Web-Based Application Development  

ENEB455

Advanced FPGA System Design using Verilog for Embedded Systems  

ENEB456

Machine Learning Tools (Machine Learning Tools)  

ENEB457

Foundations of Databases for Web Applications (Foundations of Databases for Web Applications)  
Total Credits 12

 GENERAL TRACK

The General Track offers a general focus of course content with classes from each of the three tracks.  While there are no specific required or elective courses for this track, the General Track requires 12 credits, which is the same as the other three tracks.  Consult with an advisor for details.

Sample Four Semester Plan Course Descriptions

Included Foundational Topics:  

  • Analog Circuitry 
  • Discrete Mathematics
  • Computer Organization 
  • Networks & Protocols 
  • Microelectronics 
  • Introduction to Internet of Things 
  • Coding Languages: C, Python, Java & Verilog 

Included Advanced Topics: 

  • Firmware Development
  • Real-time Operating Systems
  • Network & Hardware Security
  • Embedded Systems-focused Machine Learning
  • Individualized Year-Long Capstone Design Project 
Course Title Credits Prerequisites
ENEB302 Analog Circuits  4 PHYS 260/261, MATH 240, 241 OR 246 
ENEB304 Microelectronics and Sensors  3 ENEB302
ENEB340 Intermediate Programming Concepts and Applications for Embedded Systems (C/C++) 3  
ENEB341 Introduction to Internet of Things  3  
ENEB344 Digital Logic Design for Embedded Systems  4  
ENEB352 Introduction to Networks and Protocols  3 ENEB340
ENEB353 Computer Organization for Embedded Systems 3  
ENEB354 Discrete Mathematics for Information Technology 3 MATH141
ENEB355 Algorithms in Python 3 ENEB340 & ENEB354
ENEB408A Capstone Design Lab I 3  
ENEB408B Capstone Design Lab II 3  
ENEB454 Embedded Systems    

ENGL 393
Offered by English Dept. 

Technical Writing    

 

Course Title Credits Prerequisites
ENEB345 Probability and Statistical Inference 3  
ENEB346 Linear Algebra for Machine Learning Applications 3  MATH140
ENEB443 Hardware/Software Security for Embedded Systems 3 ENEB454
ENEB444 Operating Systems for Embedded Systems 3 ENEB340 & ENEB344
ENEB451 Network Security 3 ENEB352
ENEB452 Advanced Software for Connected Embedded Systems  3  
ENEB453 Web-Based Application Development 3  
ENEB455 Advanced FPGA Systems Design Using Verilog for Embedded Systems 3 ENEB340 & ENEB344
ENEB456 Machine Learning Tools 3  
ENEB457 Foundations of Databases for Web Applications 3 ENEB345, 352 & 355

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