SPARK: Engineer with AI
Learn to use it. Learn to question it. Learn to engineer with it.
Artificial intelligence is transforming engineering practice. SPARK — the Strategic Program for Advancing AI-Driven Research, and Knowledge — is a School of Engineering educational initiative designed to help students develop practical, responsible AI competencies for real-world engineering.
Rather than focusing primarily on building AI models from scratch, SPARK teaches engineers how to use, evaluate, verify and integrate AI tools into engineering workflows and professional decision-making.
Start with Foundations of AI in Engineering
14:440:211 | 3 credits | Spring 2027
Foundations of AI in Engineering introduces students to the practical and responsible use of artificial intelligence in engineering.
Students learn to structure AI-assisted workflows, develop effective prompts, evaluate and verify AI-generated outputs, recognize bias and failure modes, and use AI to support engineering analysis, communication and decision-making. The course also introduces foundational machine-learning and neural-network concepts at an accessible level.
No prior coding experience is required.
Prerequisite: Calculus I
Designation: School of Engineering technical/engineering elective
Meets: Mondays and Thursdays, 12:10–1:30 p.m.
Location: Richard Weeks Hall, Room 402
What You Will Learn
SPARK connects AI literacy with engineering practice. In Foundations of AI in Engineering, students explore:
- AI-assisted engineering workflows
- Generative AI systems and large language models in engineering
- Structured prompting for technical and engineering tasks
- Evaluation, verification and documentation of AI-generated outputs
- Foundational supervised and unsupervised machine-learning concepts
- Neural networks and emerging agentic AI concepts
- Bias, credibility, ethics, governance and responsible AI use
- Human-in-the-loop decision-making and engineering judgment
- AI-assisted engineering communication and documentation
- Industry-informed applications across engineering disciplines
AI Needs Engineering Judgment
Using AI effectively isn't simply about generating an answer. Engineers need to know how to assess its credibility, recognize its limitations, verify its outputs and determine when human engineering judgment must take precedence.
SPARK puts those skills at the center of AI education.
The SPARK Pathway
Students can build their AI competencies through a sequence of engineering-focused courses:
14:440:211 — Foundations of AI in Engineering
Foundational AI literacy, AI-assisted engineering workflows, prompting, verification, responsible AI use and conceptual machine learning.
14:440:212 — AI Ethics, Accountability, and Security in Engineering Practice
Ethics, bias and fairness, accountability, governance, privacy, intellectual property, security, and policy and regulatory considerations.
14:440:390 — AI Tools for Engineering Applications
Applied use of AI-assisted machine-learning tools in engineering analysis, modeling, verification and decision-making.
Approved discipline-specific AI engineering course
Apply and deepen AI knowledge within an engineering discipline.
Earn SPARK Micro-credentials
Each SPARK course includes an associated micro-credential opportunity.
To qualify for the micro-credential associated with a SPARK course, students must:
- Earn a grade of B or higher in the course; and
- Complete an additional AI-in-engineering project aligned with that course's content and competencies.
Students can pursue individual SPARK courses and their associated micro-credentials while building toward the broader SPARK pathway.
Ready to engineer with AI?
Begin with 14:440:211 — Foundations of AI in Engineering in Spring 2027.