AI Agents

Course Overview

This course provides a comprehensive, hands-on masterclass in building autonomous, multi-agent AI systems from the ground up. You will progress from core LLM foundations and API integrations to constructing complex stateful agents, workflows, and multi-agent systems using LangChain and LangGraph . Through real-world integrations—such as Telegram bots, automated email assistants, and Tavily web search engines—you will acquire the practical skills needed to design, visualize, control, and deploy production-ready AI agents.

Key Learning Outcomes

• Fundamentals & Concepts: Understand the core differences between standalone LLM models and dynamic AI agent architectures.
• LLM Setup & Tool Integration: Configure development environments, manage API keys (via OpenRouter), secure environment variables, and create custom tools for LLMs.
• Real-World Agent Deployment: Build functional production-style agents capable of interacting via Telegram, sending emails with Python, and performing web searches using Tavily.
• Graph-Based Agent Orchestration: Master LangGraph concepts including nodes, conditional routing edges, parallel execution, and graph visualization/plotting.
• State Management & Human-in-the-Loop: Manage complex graph state, incorporate custom schemas, implement sub-agents, supervisor architectures, and build human-in-the-loop validation checkpoints