Agentic AI Unleashed: Crafting LLM Applications with AutoGen Training Course

1. Introduction to LLM Applications and AutoGen v0.4

• Overview of Large Language Models (LLMs): Gaining insight into their capabilities and typical applications. 
• Introduction to AutoGen v0.4: Discovering its features, underlying architecture, and how it streamlines the development of agentic AI systems.

2. Core Concepts and Components of AutoGen

• Understanding the Layered Framework:
  • Core Layer: Examining the event-driven architecture that supports dynamic workflows.
  • AgentChat API: Constructing task-driven agents via high-level APIs.
  • Extensions: Integrating custom agents, tools, and memory modules to expand functionality.
• Asynchronous Messaging: Implementing event-driven and request-response interaction patterns. 

3. Building Your First Multi-Agent Application

• Defining Agents: Creating Assistant and User Proxy agents. 
• Establishing Agent Communication: Configuring asynchronous messaging channels between agents. 
• Implementing a Sample Application: Developing a basic multi-agent system to resolve a specific task. 
• Observability and Debugging Tools: Leveraging built-in metric tracking and message tracing for real-time oversight. 

4. Case Studies and Best Practices

• Real-World Applications: Analyzing successful AutoGen implementations across various industries.
• Best Practices: Following guidelines for designing efficient and scalable LLM applications with AutoGen.
• Challenges and Solutions: Tackling common development hurdles and exploring effective remedies.
• Q&A

This workshop is intended for:

• software developers
• data scientists
• data engineers
• professionals with a programming background or interest in learning AI programming.