ENGR 481 - Introduction to AI in Engineering

(3 units)

Foundations of generative AI and machine learning for engineering applications. Topics include neural networks, large language models, prompt engineering, fine-tuning, and multimodal AI. Students gain hands-on experience applying AI tools to engineering problem-solving, data analysis, and design. Emphasis on ethical use, critical evaluation, and discipline-specific capstone projects. Open to all engineering disciplines at the undergraduate and graduate level.

Maximum units a student may earn: 3

Prerequisite(s): CS 138 and MATH 330; or CS 202 or CHE 245 or CEE 305 or EE 291 or ME 303

Grading Basis: Graded
Units of Lecture: 3
Offered: Every Fall and Spring

Student Learning Outcomes
Upon completion of this course, students will be able to:
1. identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics.
2. 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. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
4. function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives.

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