Prompt Engineering: A Practical Example

You’ve used ChatGPT, and you understand the potential of using a large language model (LLM) to assist you in your tasks. Maybe you’re already working on an LLM-supported application and read about prompt engineering, but you’re unsure how to translate the theoretical concepts into a practical example.

Your text prompt instructs the LLM’s responses, so tweaking it can get you vastly different output. In this tutorial, you’ll apply multiple prompt engineering techniques to a real-world example. You’ll experience prompt engineering as an iterative process, see the effects of applying various techniques, and learn about related concepts from machine learning and data engineering.

You’ll work with a Python script that you can repurpose to fit your own LLM-assisted task. So if you’d like

 

 

 

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