What will you learn in The Complete Agentic AI Engineering Course (2025) Course
-
Apply Agentic AI to real-world commercial problems using proven design patterns.
-
Architect Autonomous Agentic solutions leveraging Tools, Structured Outputs, and Memory constructs.
-
Rapidly build and deploy agents with OpenAI Agents SDK and CrewAI for code-executing workflows.
-
Create robust, repeatable pipelines with LangGraph and integrate AutoGen AgentChat/Core frameworks.
-
Harness Anthropic’s Model Context Protocol (MCP) to manage context at scale in agentic applications.
-
Deliver eight end-to-end projects—from design to deployment—demonstrating Agentic AI’s transformative power.
Program Overview
Module 1: Foundations of Agentic AI
⏳ 60 minutes
-
Core concepts: Tools, Structured Outputs, and Memory patterns.
-
Best-practice design patterns for multi-agent collaboration.
Module 2: OpenAI Agents SDK
⏳ 75 minutes
-
SDK setup and first agent creation.
-
Executing and debugging code in autonomous agents.
Module 3: CrewAI Framework
⏳ 60 minutes
-
Architecting teams of agents for complex workflows.
-
Coordination strategies and error handling.
Module 4: LangGraph Implementation
⏳ 60 minutes
-
Constructing graph-based agent pipelines.
-
Ensuring robustness and repeatable execution.
Module 5: AutoGen AgentChat & Core
⏳ 75 minutes
-
Building conversational agents with AgentChat.
-
Implementing feedback loops and self-improvement via AutoGen Core.
Module 6: Model Context Protocol (MCP)
⏳ 45 minutes
-
Integrating MCP for advanced context management.
-
Use cases with Anthropic’s open-source tools.
Module 7: Project Labs – Part I
⏳ 90 minutes
-
Projects 1–4: applying frameworks to business automation and analytics.
-
End-to-end development from problem framing to deployment.
Module 8: Project Labs – Part II & Capstone
⏳ 90 minutes
-
Projects 5–8: advanced scenarios in agentic product design.
-
Capstone: design, build, and present a full agentic solution.
Get certificate
Job Outlook
-
High Demand: Agentic AI engineers are emerging as a key role as organizations adopt autonomous workflows.
-
Career Advancement: Expertise unlocks senior roles like AI Architect, Automation Lead, and Agentic Systems Specialist.
-
Salary Potential: U.S. professionals in AI engineering with agentic skill sets often earn $130K–$170K annually.
-
Freelance Opportunities: Deep knowledge of Agent SDKs, LangGraph, and MCP opens consulting and project-based work.
Explore More Learning Paths
Deepen your expertise in agentic systems, autonomous workflows, and next-generation AI engineering with these curated programs designed to elevate your capabilities in building intelligent, self-directed AI agents.
Related Courses
-
AI Agents and Agentic AI in Python Powered by Generative AI Specialization Course – Learn how to build AI agents using Python, LLMs, and multi-step reasoning frameworks for real-world automation.
-
Agentic AI and AI Agents for Leaders Specialization Course – Understand the strategic and organizational impact of agentic AI, tailored for managers and decision-makers.
-
IBM RAG and Agentic AI Professional Certificate Course – Master retrieval-augmented generation, agentic architectures, and enterprise-level implementation techniques guided by IBM experts.
Related Reading
-
What Is Knowledge Management? – Explore how structured information systems support reasoning, retrieval, and the orchestration of complex AI agent behavior.
