This is the repository for the LinkedIn Learning course Prompt Flow: Hands-On. The full course is available from LinkedIn Learning.
In this course, Senior Staff Instructor Morten Rand-Hendriksen guides you through 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.
You have two options to follow along with the course:
- Build your own Prompt Flow from scratch and using the files in
./example-files/. - Watch the course and inspect the completed project files in
./reader-final/.
The quickest way to follow along is by opening this repo in GitHub Codespaces. This provides a preconfigured environment with Python, Docker, and all necessary dependencies and extensions installed and activated. Click the button below to open a new Codespace:
You can also clone this repo and run the app locally in your preferred IDE. To do so you need a local Python environment with all the dependencies listed in requirements.txt installed:
pip install -r requirements.txtTo run the course examples you need an OpenAI API subscription. If you want to test out the custom MistralAI integration you also need a MistralAI subscription.
Information on how to set up the necessary connections is covered in the course and can also be found in reader-final/README.md.
Morten Rand-Hendriksen
Senior Staff Instructor, Speaker, Web Designer, and Software Developer
Check out my other courses on LinkedIn Learning.