AEGIS: Learn to Build and Deploy Agentic
AI Workflow Systems
September 14, 2026
Start
5 Weeks
Online
$1,299
Cost
Course Overview
A cross-disciplinary, industry-inspired microcredential that teaches the engineering workforce how to design, deploy, and govern AI workflow agents that automate routine and advanced engineering tasks, such as data cleaning, report generation, anomaly detection, design-of-experiments planning, and document compliance checks, using a combination of open-source and enterprise-ready toolchains. Unlike a traditional chatbot, an AI agent can plan multi-step tasks, use tools, access your data, and take actions with minimal human intervention.
The course assumes no programming background. All hands-on work uses no-code platforms and visual interfaces. Participants who already use tools like ChatGPT, Copilot, or similar assistants will build on that foundation to understand what happens when AI moves from answering questions to completing tasks. Students should expect 6-8 hours of coursework, weekly.
This course was made possible through the third phase funding of the Connecticut Tech Talent Accelerator (TTA 3.0), a statewide higher education innovation challenge designed to expand AI education and workforce training. According to the governor’s office, the initiative will accelerate the development of AI-skilled talent across Connecticut, strengthening the state’s competitiveness in a rapidly evolving digital economy. UConn is one of seven colleges and universities participating.
Register now to secure your spot today.
Who is This Program Ideal For?
Licensed or practicing engineers across all disciplines (mechanical, civil, chemical, electrical, biomedical, aerospace, and other related fields) who want to understand agentic AI and identify automation opportunities in their own work. Participants should have some prior experience with generative AI tools, even if casual.
Questions?
Connect with a Program Advisor for a 1:1 Session:
Students Will Gain
- A clear mental model of what agentic AI is, how it works, and where it fits in engineering practice
- Practical experience building and testing a no-code AI agent
- A concrete, workplace-specific Agent Design Canvas (blueprint) for a real automation opportunity
- An understanding of the security, safety, and compliance considerations that matter in regulated industries
- Confidence to evaluate AI agent tools and proposals, and to advocate for responsible adoption in your organization
Students will gain a certificate of completion after successfully completing the course.
Learning Objectives
By the end of this course, participants will be able to: explain how agentic AI differs from conventional generative AI tools; analyze workflows to identify automation opportunities; build, test, and iterate on a no-code AI agent; evaluate security, compliance, and data-readiness requirements; design a deployment blueprint for a real workplace process; and communicate AI value and risks to colleagues and leadership.
The Program is Ideal For
Licensed or practicing engineers across all disciplines (mechanical, civil, chemical, electrical, biomedical, aerospace, and other related fields) who want to understand agentic AI and identify automation opportunities in their own work. Participants should have some prior experience with generative AI tools, even if casual.
Learn from Renowned Faculty
UConn offers the opportunity to learn from world-renowned faculty, including Board of Trustees Distinguished Professors, researchers, and industry experts across various disciplines. Students engage with top-tier academics in fields like business analytics, engineering, and humanities, with opportunities to connect through honors programs and research.
By learning from our renowned faculty and program, you will have:
- mentorship and guidance
- career progression and growth
- elevated education in understanding of today's challenges
- value added skills, research and engagement
George Bollas
Associate Dean for Research: College of Engineering
Director: P&W Institute for Advanced Systems Engineering
P&W Endowed Chair Professor: Chemical & Biomolecular Engineering Department
Ryan Cooper
Assistant Professor In Residence
School of Mechanical, Aerospace, and Manufacturing Engineering
Kai Yu
Assistant Professor
Biomedical Engineering Department
5 Weeks Online & Self-Paced
Under this, participants will be invited to attend a 1-hour live faculty expert led discussion and Q&A (TBD)
Modules
Week 1
Module 1: What Is Agentic AI?
- Agents vs. chatbots
- The Goal → Plan → Act → Observe loop
- Identifying automation candidates in your work
Module 2: How Agents Think
- ReAct reasoning, tool use, memory and context
- Reading agent traces to understand behavior
Week 2
Module 3: Your Data, Your Agent
- Data readiness assessment
- File formats, databases, and APIs
- Preparing engineering data for agents
Module 4: Prompt Engineering for Agents
- System instructions, guardrails, output formatting
- Hands-on prompt iteration for engineering tasks
Week 3
Module 5: Building Your First Agent
- No-code guided build: document Q&A agent with engineering references
- Testing and debugging
Module 6: Multi-Agent Systems
- Orchestration patterns (supervisor, pipeline, parallel)
- Designing agent teams for complex workflows
Week 4
Module 7: Security and Access Control
- Data exposure risks, prompt injection, credential management
- Practical safeguards for enterprise use
Module 8: Compliance and Professional Standards
- Regulatory landscape, PE liability, record-keeping
- AI policies for engineering organizations
Week 5
Module 9: Capstone - Your Deployment Blueprint
- Design a complete agent system for a real workplace process
- Peer review and iteration
Module 10: Presenting Your Case
- ROI framing, stakeholder communication, phased rollout planning
- Final presentations
Enroll by August 25, 2026
Company Cohorts Available
Why Employers Should Invest in This Training
AI is rapidly reshaping engineering work. In Connecticut alone, nearly 11,000 job postings required AI skills between Aug 2024 and Aug 2025—a 40% increase in one year. AEGIS prepares engineers to deploy AI workflow agents that automate documentation, analytics, testing, quality, and compliance processes inside real engineering environments.
Participants gain practical skills employers need today:
- Building multi-step AI workflow agents
- Using LLM orchestration frameworks
- Deploying AI securely within enterprise systems
- Translating engineering workflows into AI automation
- Applying responsible AI in regulated industries
For employers, this means faster workflows, improved productivity, and engineers who can operationalize AI—not just experiment with it. To learn more about company cohorts, please schedule a personalized meeting with Business Development Officer Lisa Reinhardt.
Connect With Us
Register Now to Secure Your Spot Today.