Requirements
This certificate requires a minimum total of 15 credits, including the required minimum
9 credits of core and primary focus courses and up to 6 credits of approved electives.
A grade of B or higher is required in all applicable courses and there is a maximum
of 6 credits at 4000-level. Credits below 4000-level are not permissible toward the
certificate.
Enrolled in Mechanical Engineering, Mechanical Eng-Eng Mechanics, Engineering Mechanics
Required Coursework (Core) 6 credits – both of the following:
Required Coursework (Primary Focus) 3 or more credits from the following:
EE 5365 - In-Vehicle Communication Networks
Course focuses on in-vehicle system domains and their requirements, and in-vehicle communication bus Controller Area Network (CAN) and its related physical layers standards. It also covers other buses such as LIN, FlexRay, MOST, Ethernet, as well as introduction to V2V and V21.
- Credits:
3.0
- Lec-Rec-Lab: (2-0-3)
- Semesters Offered:
Fall, Summer
- Restrictions:
Must be enrolled in one of the following Level(s): Graduate;
Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Computer Science, Engineering Mechanics, Mechanical Engineering, Computer Engineering, Electrical Engineering
- Pre-Requisite(s): EE 3250 or EE 4250
EE 5367 - Connected and Autonomous Vehicle Technology
Principles, technologies, standards and applications of connected and autonomous vehicles. Topics include vehicular mobility modeling, physical layer considerations, routing protocols, automotive cybersecurity, as well as autonomous vehicles sensors technologies, sensor data fusion techniques, and autonomous vehicles challenges.
- Credits:
3.0
- Lec-Rec-Lab: (2-0-3)
- Semesters Offered:
Spring
- Restrictions:
Must be enrolled in one of the following Level(s): Graduate;
Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Computer Science, Engineering Mechanics, Mechanical Engineering, Computer Engineering, Electrical Engineering
- Pre-Requisite(s): EE 5365 and EE 4272
Elective Coursework – up to 6 credits from the following:
CS 4471 - Computer Security
This covers fundamentals of computer security. Topics include practical cryptography, access control, security design principles, physical protections, malicious logic, program security, intrusion detection, administration, legal and ethical issues.
- Credits:
3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered:
Fall
- Restrictions:
May not be enrolled in one of the following Level(s): Graduate
- Pre-Requisite(s): CS 3411 or CS 4411
CS 5471 - Computer Security
This covers fundamentals of computer security. Topics include practical cryptography, access control, security design principles, physical protections, malicious logic, program security, intrusion detection, administration, legal and ethical issues.
- Credits:
3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered:
Fall, Spring
- Restrictions:
Must be enrolled in one of the following Level(s): Graduate
- Pre-Requisite(s): CS 3411 or CS 4411
CS 5472 - Advanced Topics in Computer Security
This course covers various aspects of producing trusted computer information systems. Topics include network perimeter protection, host-level protection, authentication technologies, formal analysis techniques, and intrusion detection. Current systems will be examined and critiqued.
- Credits:
3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered:
Spring
- Restrictions:
Must be enrolled in one of the following Level(s): Graduate
- Pre-Requisite(s): CS 4471 or CS 5471 or SAT 4520
CS 5821 - Computational Intelligence - Theory and Application
This course covers the four main paradigms of Computational Intelligence, viz., fuzzy systems, artificial neural networks, evolutionary computing, and swarm intelligence, and their integration to develop hybrid systems. Applications of Computational Intelligence include classification, regression, clustering, controls, robotics, etc.
- Credits:
3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered:
On Demand
- Restrictions:
Permission of instructor required;
Must be enrolled in one of the following Level(s): Graduate
CS 5841 - Machine Learning
This course will explore the foundational techniques of machine learning. Topics are pulled from the areas of unsupervised and supervised learning. Specific methods covered include naive Bayes, decision trees, support vector machine (SVMs), ensemble, and clustering methods.
- Credits:
3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered:
Spring
- Restrictions:
Permission of instructor required;
May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior
- Pre-Requisite(s): CS 4821
Enrolled in Computer Engineering, Electrical Engineering
Required Coursework (Core) 6 credits – both of the following:
EE 5455 - Cybersecurity of Industrial Control Systems
General introduction to cybersecurity of industrial control systems and critical infrastructures. Topics include NIST and DHS publications, threat analysis, vulnerability analysis, red teaming, intrusion detection systems, industrial networks, industrial malware, and selected case studies.
- Credits:
3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered:
On Demand
- Restrictions:
Must be enrolled in one of the following Level(s): Graduate;
Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Cybersecurity, Mechatronics, Computer Science, Computer Engineering, Electrical Engineering
EE 5315 - Cyber Security of Automotive Systems I
Modern automotive control and communications systems from a cyber security perspective. Topics include: V2X communications, vehicle attack surfaces and vulnerabilities, in-vehicle networks, threat analysis and vulnerabilities, security mechanisms and architectures, security requirements analysis, hardware security modules, and standards.
- Credits:
3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered:
Spring
- Restrictions:
Must be enrolled in one of the following Level(s): Graduate;
Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Computer Science, Mechanical Engineering, Mechatronics, Mechanical Eng-Eng Mechanics, Computer Engineering, Electrical Engineering
- Pre-Requisite(s): MEEM 5300 or ME 5300 or EE 5455
Required Coursework (Primary Focus) 3 or more credits from the following:
EE 5365 - In-Vehicle Communication Networks
Course focuses on in-vehicle system domains and their requirements, and in-vehicle communication bus Controller Area Network (CAN) and its related physical layers standards. It also covers other buses such as LIN, FlexRay, MOST, Ethernet, as well as introduction to V2V and V21.
- Credits:
3.0
- Lec-Rec-Lab: (2-0-3)
- Semesters Offered:
Fall, Summer
- Restrictions:
Must be enrolled in one of the following Level(s): Graduate;
Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Computer Science, Engineering Mechanics, Mechanical Engineering, Computer Engineering, Electrical Engineering
- Pre-Requisite(s): EE 3250 or EE 4250
EE 5367 - Connected and Autonomous Vehicle Technology
Principles, technologies, standards and applications of connected and autonomous vehicles. Topics include vehicular mobility modeling, physical layer considerations, routing protocols, automotive cybersecurity, as well as autonomous vehicles sensors technologies, sensor data fusion techniques, and autonomous vehicles challenges.
- Credits:
3.0
- Lec-Rec-Lab: (2-0-3)
- Semesters Offered:
Spring
- Restrictions:
Must be enrolled in one of the following Level(s): Graduate;
Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Computer Science, Engineering Mechanics, Mechanical Engineering, Computer Engineering, Electrical Engineering
- Pre-Requisite(s): EE 5365 and EE 4272
EE 5750 - Model-Based Embedded Control System Design
This course introduces embedded control system design using a model-based approach. Course topics include model-based embedded control system design, discrete-event control, sensors, actuators, electronic control unit, digital controller design, and communication protocols. Prior knowledge of hybrid electric vehicles is highly recommended.
- Credits:
3.0
- Lec-Rec-Lab: (0-2-2)
- Semesters Offered:
Fall
- Restrictions:
Must be enrolled in one of the following Level(s): Graduate;
Must be enrolled in one of the following Major(s): Electrical Engineering, Electrical & Computer Engineer
- Pre-Requisite(s): MEEM 4700 or ME 4700 or MEEM 4775 or ME 4775 or EE 3261 or EE 4261
EE 5811 - Automotive Systems
Automotive systems for light duty vehicles are examined from the perspectives of requirements, design, technical, and economic analysis for advanced mobility needs. This course links the content for the automotive systems graduate certificate in controls, powertrain, vehicle dynamics, connected and autonomous vehicles.
- Credits:
3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered:
Fall
- Restrictions:
Must be enrolled in one of the following Level(s): Graduate;
Must be enrolled in one of the following Major(s): Automotive Systems & Controls, Electrical Engineering, Computer Engineering, Electrical & Computer Engineer
EE 5812 - Automotive Control Systems
Introduction to automotive control systems. Modeling and control methods are presented for: air-fuel ratio, transient fuel, spark timing, idle speed, transmission, cruise speed, anti-lock brakes, traction, active suspension systems, and hybrid electric vehicles, Advanced control methodologies are introduced for appropriate applications.
- Credits:
3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered:
Spring
- Restrictions:
Must be enrolled in one of the following Level(s): Graduate;
Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Electrical Engineering, Computer Engineering
- Pre-Requisite(s): EE 3261 or MEEM 4775 or ME 4775
EE 6320 - Cyber Security of Automotive Systems II
This course covers advanced topics in cyber security of automotive systems. Topics include modeling and simulation of cyber attacks on vehicle subsystems, communications security for V2X systems, vulnerabilities in cooperative vehicle infrastructures, threat analysis, and cyber security of SAE level 2, 3, and 4 autonomous driving systems.
- Credits:
3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered:
Fall
- Restrictions:
Must be enrolled in one of the following Level(s): Graduate;
Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Computer Science, Mechanical Engineering, Mechanical Eng-Eng Mechanics, Computer Engineering, Electrical Engineering;
Must be enrolled in one of the following Campus(s): Co-op and Online Course(s), Co-op Program, Off Campus, Off Campus MTU On-Line
- Pre-Requisite(s): MEEM 5310 or EE 5310
Elective Coursework – up to 6 credits from the following:
CS 4471 - Computer Security
This covers fundamentals of computer security. Topics include practical cryptography, access control, security design principles, physical protections, malicious logic, program security, intrusion detection, administration, legal and ethical issues.
- Credits:
3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered:
Fall
- Restrictions:
May not be enrolled in one of the following Level(s): Graduate
- Pre-Requisite(s): CS 3411 or CS 4411
CS 5471 - Computer Security
This covers fundamentals of computer security. Topics include practical cryptography, access control, security design principles, physical protections, malicious logic, program security, intrusion detection, administration, legal and ethical issues.
- Credits:
3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered:
Fall, Spring
- Restrictions:
Must be enrolled in one of the following Level(s): Graduate
- Pre-Requisite(s): CS 3411 or CS 4411
CS 5472 - Advanced Topics in Computer Security
This course covers various aspects of producing trusted computer information systems. Topics include network perimeter protection, host-level protection, authentication technologies, formal analysis techniques, and intrusion detection. Current systems will be examined and critiqued.
- Credits:
3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered:
Spring
- Restrictions:
Must be enrolled in one of the following Level(s): Graduate
- Pre-Requisite(s): CS 4471 or CS 5471 or SAT 4520
EE 5821 - Computational Intelligence - Theory and application
This course covers the four main paradigms of Computational Intelligence, viz., fuzzy systems, artificial neural networks, evolutionary computing, and swarm intelligence, and their integration to develop hybrid systems. Applications of Computational Intelligence include classification, regression, clustering, controls, robotics, etc.
- Credits:
3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered:
On Demand
- Restrictions:
Permission of instructor required;
Must be enrolled in one of the following Level(s): Graduate
EE 5841 - Machine Learning
This course will explore the foundational techniques of machine learning. Topics are pulled from the areas of unsupervised and supervised learning. Specific methods covered include naive Bayes, decision trees, support vector machine (SVMs), ensemble, and clustering methods.
- Credits:
3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered:
Spring
- Restrictions:
Permission of instructor required;
May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior
Online Delivery
This certificate is available online. All the core required courses are offered online. Elective courses are regularly
taught on campus and will be placed online based on demand. This allows off-campus
students to fully complete the Graduate Certificate in Safety and Security of Autonomous
Cyber-Physical Systems online.
