Building Agentic AI Systems

Design, Orchestrate, and Deploy Intelligent AI Agents for Real-World Workflows

Building Agentic AI Systems is a hands-on, project-driven course that equips you with the skills to design and implement intelligent AI agents capable of reasoning, planning, and taking action. The course introduces the core foundations of agentic AI, including tool use, memory, and multi-step reasoning, before guiding you through practical implementation using modern frameworks such as CrewAI and LangGraph.

With a strong emphasis on a design-first approach, you will analyze real-world problems, determine when agent-based solutions are appropriate, and architect both single-agent and multi-agent systems. By the end of the course, you will build and present a working agentic AI prototype that automates or enhances a real-world workflow.

What You Will Learn
 

• Explain core concepts of agentic AI, including tool use, planning, memory, and reasoning
• Differentiate agentic AI systems from traditional large language model (LLM) prompting
• Design agent-based solutions aligned to real-world problems and workflows
• Build functional AI agents using CrewAI with integrated tools, APIs, and data sources
• Orchestrate multi-agent systems using LangGraph with routing and state management
• Apply human-in-the-loop patterns for oversight and control
• Evaluate agent performance for reliability, safety, and risk
• Develop and present a real-world agentic AI capstone project

Topics Covered
 

• Introduction to Agentic AI and the Agent Landscape
• Agentic Design Patterns (ReAct, Plan-and-Execute, Human-in-the-Loop)
• AI Agent Frameworks: CrewAI, LangGraph, and Emerging Tools
• Building Single-Agent Systems with Tool Integration
• Agent Memory, State Management, and RAG
• LangGraph Fundamentals: Graphs, Nodes, Edges, and State
• Multi-Agent Orchestration: Routing, Handoffs, and Parallel Execution
• AI-Assisted Development Environments 
• Agent Evaluation, Testing, and Risk Management
• Capstone Project Development