Building Advanced AI Apps with Prompt Flow
36mGeneral2024-09-11
Authors
Morten Rand-Hendriksen
Senior Staff Instructor, Speaker, Web Designer, and Software Developer
Course details
In this course, Senior Staff Instructor Morten Rand-Hendriksen guides you through developing LLM-based AI apps using the open-source Prompt Flow suite. Get hands-on practice creating, analyzing, and evaluating workflows that link LLMs, prompts, and Python code. With real-world examples and practical insights, Morten helps you master prompt engineering, streamlining development, and getting started orchestrating advanced AI projects.
Learning objectives
Examine the capabilities of Prompt Flow.
Create flows that leverage LLMs, Python code, and tools to produce streamlined workflows.
Evaluate flows for efficiency, functionality, and robustness.
Explore the Prompt Flow GitHub repo and its examples and documentation.
Develop custom flows with advanced prompt engineering techniques and integrated tools.
Learning objectives
Examine the capabilities of Prompt Flow.
Create flows that leverage LLMs, Python code, and tools to produce streamlined workflows.
Evaluate flows for efficiency, functionality, and robustness.
Explore the Prompt Flow GitHub repo and its examples and documentation.
Develop custom flows with advanced prompt engineering techniques and integrated tools.
Skills covered
Programming FoundationsGenerative AIArtificial Intelligence FoundationsSoftware Development ToolsArtificial Intelligence (AI)Software DevelopmentOne-Off
Concepts
0. Introduction
- 01 - Prompt Flow - Your toolkit to build AI apps
1. Exploring Prompt Flow
- 02 - What is Prompt Flow
- 03 - Exploring the Prompt Flow repo in Codespaces
- 04 - Exploring the Prompt Flow VS Code extension
- 05 - Creating a connection to OpenAI
- 06 - Running Prompt Flow examples
- 07 - Anatomy of a Prompt Flow
- 08 - Prompt variants
- 09 - Batch testing of flows
2. Conclusion
- 10 - Going further with Prompt Flow