Agentic AI: Fundamentals, Frameworks & Hands-On Projects
Learn how to build intelligent AI agents that can reason, make decisions, use tools, and execute tasks with greater autonomy.
This practical Agentic AI course takes you from understanding the fundamentals of AI agents to developing multi-agent systems and automated workflows. Explore modern frameworks and tools, including LangChain, LangGraph, AutoGen, CrewAI, Groq API, Cursor AI, and Claude.
Through hands-on demonstrations and development projects, you will learn how AI agents operate, collaborate, interact with external tools, and support real-world applications.
The course also introduces AI agent observability, workflow automation, application development, career opportunities, and interview preparation.
What You’ll Learn
- Understand Agentic AI and AI Agent fundamentals
- Learn how agents reason, plan, remember, and take actions
- Understand single-agent vs multi-agent systems
- Work with LangGraph, LangChain, AutoGen, and CrewAI
- Build agents that can use tools and execute functions
- Understand short-term and long-term agent memory
- Design multi-agent collaboration and delegation workflows
- Build practical AI agents and workflow automations
- Understand agent observability and monitoring
- Develop hands-on Agentic AI projects
Curriculum
- 6 Sections
- 29 Lessons
- 4 Weeks
- Module 1: Foundations of Agentic AI7 ItemsUnderstand the fundamentals of Agentic AI, how intelligent agents differ from traditional AI systems, and how they make decisions and interact with their environments. Get started with practical implementations, including a simple AI chatbot and an email agent.
- Module 2: Agent Architectures & Frameworks4 ItemsExplore the architecture of AI agents, the differences between single-agent and multi-agent systems, and popular development frameworks. Learn how to implement a multi-agent system using the AutoGen library.
- Module 3: LLM-Powered Agents4 ItemsDiscover how Large Language Models power intelligent agents through prompting, reasoning, decision-making, and tool integration. Build practical AI agents using LangGraph and LangChain.
- Module 4: Multi-Agent Collaboration4 ItemsLearn how multiple AI agents communicate, coordinate tasks, and work together to achieve shared objectives. Explore agent interaction, conflict management, and collaborative workflows through practical examples.
- Module 5 — Hands-on Agent Development6 ItemsApply your knowledge through practical projects involving multi-agent development, AI-powered application building, system monitoring, and workflow automation. Work with tools and frameworks including LangGraph, CrewAI, Cursor AI, Claude, and Antigravity.
- 5.15.1 – Hands-On Project: Multi-Agent System Using LangGraph
- 5.25.2 – Observability: Monitoring with Gravitee and Dynatrace
- 5.35.3 – Cursor AI: Building an Android Wishing App
- 5.45.4 – Workflow Automation Using CrewAI – Part 1
- 5.55.4 – Workflow Automation Using CrewAI – Part 2
- 5.65.5 – Web Application Project Using Claude, Antigravity and Requestly
- Module 6: Career Opportunities in Agentic AI4 ItemsExplore career opportunities in the growing field of Agentic AI and prepare for technical interviews. Understand relevant career paths, interview topics, and recommended practices for developing AI agent systems.
Agentic AI: Fundamentals, Frameworks & Hands-On Projects
Learn how to build intelligent AI agents that can reason, make decisions, use tools, and execute tasks with greater autonomy.
This practical Agentic AI course takes you from understanding the fundamentals of AI agents to developing multi-agent systems and automated workflows. Explore modern frameworks and tools, including LangChain, LangGraph, AutoGen, CrewAI, Groq API, Cursor AI, and Claude.
Through hands-on demonstrations and development projects, you will learn how AI agents operate, collaborate, interact with external tools, and support real-world applications.
The course also introduces AI agent observability, workflow automation, application development, career opportunities, and interview preparation.
What You’ll Learn
- Understand Agentic AI and AI Agent fundamentals
- Learn how agents reason, plan, remember, and take actions
- Understand single-agent vs multi-agent systems
- Work with LangGraph, LangChain, AutoGen, and CrewAI
- Build agents that can use tools and execute functions
- Understand short-term and long-term agent memory
- Design multi-agent collaboration and delegation workflows
- Build practical AI agents and workflow automations
- Understand agent observability and monitoring
- Develop hands-on Agentic AI projects
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