AI
Agentic AI in Action: Building and Orchestrating Agents
This hands-on follow-on course builds on the foundational Introduction to Agentic AI session.
Participants will move from theory to practical demonstrations, exploring how agentic systems can be implemented using popular workflow and automation tools. Through guided demos and discussions, you will see how concepts like orchestration, tool use, and inter-agent communication come alive across real platforms such as n8n, Zapier, and Google Opal.
The class also surveys emerging low-code and enterprise frameworks – including LangFlow, CrewAI, and OpenAI AgentKit – to illustrate how organizations are operationalizing agentic AI within secure, governed environments.
This course is included in the AI Learning Subscription.
Duration
½ day
Audience
- AI, data science, and automation professionals who completed Intro to Agentic AI
- Technical managers or solution architects exploring agent orchestration frameworks
- Developers, analysts, and business innovators seeking to prototype AI agents rapidly
- Educators and government professionals evaluating agentic workflows for operations or training programs
Learning Objectives
- Experience agentic AI in action: Watch live demos of no-code and low-code agent orchestration tools.
- Bridge theory to practice: Connect concepts like orchestration loops, MCP, and A2A to real workflow automation.
- Explore the vendor ecosystem: See how OpenAI, Anthropic, Perplexity, and Google are shaping the agentic landscape.
- Learn how to evaluate frameworks: Understand where tools like LangFlow, CrewAI, and AgentOps fit into enterprise AI stacks.
- Prepare for adoption: Gain insight into scaling, governance, and integration best practices for agent systems.
After completing this class, participants will be able to:
- Describe the key components of agent orchestration, including perception, reasoning, action, and feedback.
- Configure and run basic agent workflows using n8n and Zapier.
- Explain how protocols like MCP and A2A enable interoperability among AI agents.
- Compare and contrast low-code agent frameworks (LangFlow, CrewAI) and identify enterprise considerations.
- Evaluate emerging agentic AI solutions from major LLM providers and discuss their implications for business adoption.
1. Concept Review
- Quick recap: AI Assistant vs. AI Agent
- The orchestration loop (Perception → Reasoning → Action → Feedback)
- Tools, extensions, and data stores
- MCP and A2A (review of interoperability concepts)
- SLM + LLM layering (why most real agentic systems use both)
- Brief intro to workflow orchestration tools (Zapier, n8n, LangFlow, Opal)
2. Demos
Goal: Show how agentic orchestration happens in practice, starting from no-code tools up to emerging agent frameworks.
- Demo 1: n8n as an Agent Orchestrator
- Demo 2: Zapier AI Actions and Natural-Language Workflows
- Demo 3: Google Opal and the Future of Agent Collaboration
3. Discussion: Beyond No-Code
- OpenAI AgentKit, Perplexity Comet AI browser, Google Agent Development Kit, etc.
- LangFlow, CrewAI, and other low-code frameworks
- Why they’re powerful but harder to deploy in enterprise settings
- AgentOps, evaluation, and observability (brief introduction)
- Open standards convergence: MCP, A2A, FIPA-like coordination
- Where enterprise adoption is heading (IBM, Google, Microsoft)
4. Wrap-Up + Q&A
Is there a discount available for current students?
UMBC students and alumni, as well as students who have previously taken a public training course with UMBC Training Centers are eligible for a 10% discount, capped at $250. Please provide a copy of your UMBC student ID or an unofficial transcript or the name of the UMBC Training Centers course you have completed. Asynchronous courses are excluded from this offer.
What is the cancellation and refund policy?
Student will receive a refund of paid registration fees only if UMBC Training Centers receives a notice of cancellation at least 10 business days prior to the class start date for classes or the exam date for exams.