Course curriculum

  • 1
    Introduction to AI Agents and Multi-Agent Systems
    • Course Handouts
    • Understanding AI Agents
    • Types of AI Agents
    • Single-Agent vs. Multi-Agent Systems
    • Introduction to the Hotel Support Project
    • Project Architecture
    • Required Tools and Frameworks
    • Quiz
  • 2
    Agent-Based Hotel Reservation System
    • Project Environment Setup
    • Agent 1 - Customer Conversation Specialist
    • Agent 2 - Hotel Reservation System Handler
    • Agent 3 - Compliance Checker
    • Handling Edge Cases and Errors
    • Testing our System
    • Quiz
  • 3
    Advanced AI Agent Orchestration
    • Advanced Agents Orchestration
    • Advanced Agent-to-Agent Communication
    • Adding Advanced Agents (Optional Extensions) - Sentiment Analysis
    • Adding Advanced Agents (Optional Extensions) - Web Search
    • Adding Advanced Agents (Optional Extensions) - MultiLanguage
    • System-Wide Error Handling
    • Quiz

Course Description

Bring AI agents to life with “Building a Multi-Agent AI System for Hotel Reservations,” a practical, project-based course that walks you through designing and deploying a real-world AI solution. Learn how to architect multi-agent workflows, implement specialized agents like conversation managers and compliance checkers, and orchestrate seamless interactions using LangGraph and modern AI frameworks. From database integration to web deployment, this hands-on course gives you the tools to solve real problems with collaborative AI.

Who Should Enroll

  • AI enthusiasts ready to go beyond chatbots and into orchestration

  • Product builders prototyping AI-driven solutions for hospitality or service ops

  • Students and professionals seeking hands-on experience with LangGraph and agent tooling

  • Developers & engineers eager to build real-world multi-agent AI systems

  • Tech leaders exploring scalable AI automation in customer workflows

Key Takeaways

  • Build a Real-World Multi-Agent AI System for hotel reservations using LangGraph and modern LLM tools.

  • Design Specialized Agents for conversations, database handling, compliance checks, and more.

  • Enable Inter-Agent Communication with coordinated workflows and intelligent task orchestration.

  • Handle Errors and Edge Cases with robust strategies for recovery and system stability.

  • Deploy Your Project as a scalable web app using Docker, Gradio, and cloud platforms.

About the Instructor

Dr. Vasilii Ganishev - Lead Data Scientist, Automative Industry - Germany

Dr. Vasilii Ganishev is an experienced data scientist and machine learning expert with over 5 years of hands-on experience in deep learning, data analysis, and statistics. With a PhD in Software Engineering, Dr. Ganishev has a solid foundation in computer science, having worked extensively with programming languages such as Python, R, and Java. His deep understanding of complex algorithms and real-world problem-solving makes him an excellent instructor for both beginner and advanced learners in the AI and machine learning domains.
About the Instructor

FAQ

  • What prior knowledge is required to enroll in this course?

    This course assumes basic knowledge of Python and AI concepts. Familiarity with APIs, databases, and web frameworks (like Flask or FastAPI) is helpful but not required.

  • Do I need to have prior experience with LangGraph?

    Address common questions ahead of time to save yourself an email.

  • Will I get hands-on experience with deployment?

    Yes! You will deploy your AI system both locally and on the cloud using LangGraph, Gradio, and Docker, giving you real-world deployment skills.

  • Is this course suitable for beginners in AI?

    While some basic programming knowledge is required, this course is designed to be accessible to learners who have a foundational understanding of AI and want to advance their skills in agent-based systems.

  • What tools and frameworks will I be using in this course?