Artificial Intelligence and Machine Learning for Engineering Applications (Certificate)

Location(s): Main Campus

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Program Summary

The Certificate of Proficiency in Artificial Intelligence and Machine Learning for Engineering Applications is designed to equip engineering professionals, including seasoned veterans and recent graduates, with the knowledge and skills necessary to leverage cutting-edge AI and ML techniques in engineering contexts. The program focuses on the practical application of AI and ML methodologies to solve real-world engineering challenges across various domains such as predictive maintenance, malfunction detection, computer vision and autonomous vehicles, etc.

Program Information

All courses must be passed with a “C-” (1.7) or better to be counted in the certificate.
Students must earn a minimum overall GPA of 2.0 to be awarded the certificate.

Certificate Completion

This certificate program may be completed independently and does not require enrollment in or completion of any degree program to be awarded.

Artificial Intelligence and Machine Learning for Engineering Applications Curriculum (19 Credits)

Core Requirements (16 Credits)

ENGR 2170 - Programming for Engineers 3 Credit(s)
MATH 1210 - Calculus I 4 Credit(s)
ME 3600 - Introduction to AI and Machine Learning for Engineers 3 Credit(s)
ME 3620 - Introduction to Computer Vision for Engineers 3 Credit(s)
ME 4600 - Artificial Intelligence for Predictive Maintenance 3 Credit(s)

Capstone Course (3 Credits)

Complete one of the following:

ENGR 4860 - Artificial Intelligence Practicum 3 Credit(s)
ME 4055 - Capstone Design 3 Credit(s)

Total Credits, Certificate: 19

Program Learning Outcomes

Proficiency in AI and ML Applications in Engineering: Upon completion of the program, students will demonstrate a proficient understanding of artificial intelligence and machine learning concepts, methodologies, and tools, enabling them to apply these skills effectively in engineering contexts such as machine learning algorithms, computer vision techniques, and predictive maintenance utilizing AI technologies.
Problem-Solving and Critical Thinking: Graduates will exhibit advanced problem-solving abilities and critical thinking skills within the realm of AI and ML in engineering. They will be capable of analyzing complex engineering challenges, formulating innovative AI-based solutions, and evaluating the efficacy of these solutions in real-world scenarios.
Collaboration and Interdisciplinary Competence: Students completing the program will showcase competence in interdisciplinary collaboration, being able to communicate and work effectively with professionals from diverse fields. This outcome will empower graduates to contribute meaningfully to multidisciplinary teams, driving innovation in engineering projects that incorporate AI and ML applications.