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AI Agents Essentials: Practical Enterprise AI Capability Building
A practical, business-focused program introducing AI Agents: intelligent systems capable of reasoning, planning, using tools, retrieving knowledge, collaborating with other agents and executing multi-step business workflows. Covers Agentic AI, tool calling, memory, RAG, MCP, multi-agent systems, human-in-the-loop governance and enterprise adoption.
Six capabilities this program builds so you can design and deploy AI agents responsibly.
Explain how AI agents differ from chatbots, copilots and traditional automation.
Design AI agent workflows using reasoning, planning, memory and tool use.
Connect AI agents to enterprise knowledge using Retrieval-Augmented Generation.
Integrate AI agents with enterprise tools and APIs using MCP and tool calling.
Build human-in-the-loop approval workflows and apply AI security controls.
Prototype an AI agent solution and plan its enterprise rollout.
How the program moves you from core Agentic AI concepts to a capstone agent you build and present.
Learn Agentic AI concepts and enterprise architectures.
Watch AI agents perform real multi-step business workflows.
Design agent architecture, prompts and workflow maps.
Connect agents to enterprise tools, APIs and knowledge sources.
Practice multi-agent collaboration and automation scenarios.
Design and present a complete enterprise AI agent solution.
Learn Agentic AI concepts and enterprise architectures.
Watch AI agents perform real multi-step business workflows.
Design agent architecture, prompts and workflow maps.
Connect agents to enterprise tools, APIs and knowledge sources.
Practice multi-agent collaboration and automation scenarios.
Design and present a complete enterprise AI agent solution.
The functional agent scenarios you'll design, pulled directly from the program's applied curriculum.
Design and present a complete AI Agent Solution: agent architecture, reasoning workflows, memory strategy, RAG integration, MCP-based tool access, human approval checkpoints and an implementation roadmap.
The program focuses on the concepts behind MCP, RAG and multi-agent design, not any single framework.
ChatGPT · Copilot · Claude · Gemini · Perplexity · Azure AI Foundry
OpenAI Agents SDK · Microsoft AutoGen · LangChain · LangGraph · LlamaIndex · CrewAI
MCP · RAG · Function calling · Vector databases · Knowledge graphs
Power Automate · n8n · Zapier · Make · REST APIs
Agent Design · Lifecycle · Human-in-the-Loop · Security · Evaluation · Adoption
A preview of the modules inside the program. See the full breakdown in the detailed curriculum.
AI Agents, Agentic AI, and how they differ from chatbots, copilots and traditional workflows.
Reasoning, planning, memory, tool use, actions and feedback loops.
System prompts, goals, constraints, instructions; sequential, conditional, event-driven and autonomous workflows.
Short-term, long-term and semantic memory; connect agents to enterprise knowledge with Retrieval-Augmented Generation.
Model Context Protocol, APIs, enterprise tools and function calling.
Agent orchestration, collaboration, delegation and coordination.
Apply AI agents in HR, Finance, Sales, Marketing, Operations, Customer Service and IT.
Approval workflows, escalation, exception handling and Responsible AI for agents.
Prompt injection, permissions, identity, access, data protection; agent testing, tracing and quality metrics.
Governance, operating models, implementation roadmaps; prototype an AI agent solution for a real business workflow.
Hands-on workshop to build, test, and deploy multi-step agentic workflows using modern frameworks and enterprise tools.
Architect multi-agent systems, error recovery, deterministic guardrails, human-in-the-loop triggers, and enterprise integration.
Customized capability journey for engineering and innovation teams scaling secure agentic automation across enterprise systems.
Every module, topic, activity and practical application, laid out in the detailed curriculum.