AI Orchestration: Foundations

Course details

This course outlines how to design and build more complex LLM applications, showcasing the importance of orchestration as part of the process. Topics covered include the components of AI orchestrators, including input and output interfaces, prompt chaining, APIs, AI workflows and agents, and specialized LLMs. Along the way, instructor Denys Linkov shows you how to orchestrate AI to create and manage a simple AI-powered coaching app.

Learning objectives
Understand the importance of AI orchestration.
Identify use cases where AI orchestration is helpful, including AI coach, customer support, internal knowledge base, and sales lead generation.
Describe the key parts of an AI orchestrator.
Build a simple application that leverages AI orchestration.

Concepts

0. Introduction

01 - Learn the basics of AI orchestration
02 - Setting up your environment

1. Why Use AI Orchestration

03 - When using ChatGPT isn't enough
04 - What is AI orchestration, and why is it useful
05 - Architecture of AI orchestrators

2. Components of an AI Orchestrator

06 - Input interface for AI orchestrators
07 - Output interfaces for AI orchestrators
08 - Orchestrating LLMs with prompt chaining
09 - Calling APIs and connecting to databases
10 - AI workflows and agents
11 - Specialized large language models (LLMs)

3. AI Orchestration for a Basic AI App

12 - Building low-code vs. code
13 - Visualizing an AI orchestration framework
14 - Building a simple AI app
15 - Implementing multiple AI workflows
16 - Adding API calls to your AI app
17 - Challenge - Building an AI coach
18 - Solution - Building an AI coach

Conclusion

19 - Conclusion