SPARK Your AI Knowledge

Explore the SPARK Course Pathway

SPARK offers a four-course sequence that builds AI knowledge and skills, from foundational concepts to discipline-specific engineering applications.

1. Foundations of AI in Engineering (14:440:211)

   Develop foundational AI literacy and learn to use AI-assisted engineering workflows, structured prompting, and techniques for evaluating and verifying AI-generated outputs. Explore introductory machine-learning concepts and responsible AI use.

2. AI Ethics, Accountability, and Security in Engineering Practice (14:440:212)

   Examine the ethical, legal and security considerations surrounding AI in engineering, including bias, fairness, accountability, privacy, intellectual property and governance.

3. AI Tools for Engineering Applications (14:440:390)

   Explore the practical use of AI-assisted machine-learning tools for engineering analysis, modeling, verification and decision-making.

4. Discipline-Specific AI Engineering Course

   Deepen your understanding of AI through an approved course focused on applications within your engineering discipline.

Earn SPARK Micro-Credentials

You don't have to complete all four courses to pursue a SPARK micro-credential.

Each SPARK course provides an opportunity to earn a course-specific micro-credential that recognizes competency in a focused area of AI-enabled engineering practice.

To qualify for a micro-credential, students must:

• Earn a grade of B or higher in the associated course.
• Complete an additional AI-in-engineering project aligned with the course's content and competencies.

Students can pursue individual micro-credentials as they progress through the SPARK pathway, building a record of their developing AI knowledge and skills.

Why SPARK?

AI is increasingly integrated into engineering practice. Engineers need more than familiarity with AI tools; they need the judgment and skills to apply them effectively and responsibly.

Through SPARK, students can:

• Build practical AI skills. Learn how to use AI tools in engineering workflows and professional applications.
• Strengthen engineering judgment. Develop the ability to evaluate, verify and critically assess AI-generated information.
• Explore responsible AI. Understand bias, ethics, accountability and the limitations of AI technologies.
• Connect learning to industry. Explore industry-informed applications and real-world engineering challenges.
• Demonstrate competencies. Pursue course-specific micro-credentials through additional AI-in-engineering projects.

Start Your SPARK Journey in Spring 2027

Foundations of AI in Engineering

14:440:211 | 3 Credits

The first SPARK course launches in Spring 2027 for Rutgers School of Engineering students.

Foundations of AI in Engineering introduces the practical and responsible use of artificial intelligence in engineering. Students learn how to develop effective prompts, integrate AI into engineering workflows, evaluate AI-generated outputs, recognize bias and limitations, and apply AI tools to engineering analysis and decision-making.

No prior coding experience is required.

Course Information

• Semester: Spring 2027
• Credits: 3
• Designation: School of Engineering technical/engineering elective
• Prerequisite: Calculus I
• Schedule: Mondays and Thursdays, 12:10–1:30 p.m.
• Location: Richard Weeks Hall, Room 402
• Eligibility: Rutgers School of Engineering students who have completed Calculus I