A short prompt engineering (chatGPT 'cooking') course by Andrew Ng and OpenAI

In this post, I review a short course by Andrew Ng and Isa Fulford on ChatGPT Prompt Engineering for Developers.

I found “ChatGPT Prompt Engineering for Developers” great and would like to give a short overview.

It’s our favorite Andrew Ng in collaboration with Isa Fulford from OpenAI.

Hi, Andrew! Long time no see! image credit


  • the course is (yet) free
  • the course is very short, just ~10 lectures, 5-10 min. each
  • very practical, it’s all about examples of using OpenAI APIs
  • the platform is great: video on the right, and interactive Jupyter running on the left; thus you can play around with code while watching the video

Some tips covered

  • tiny ones like putting the part of the text that you need to process between triple backticks
  • making chatGPT respond in a structured way, e.g. JSON so that you don’t have to parse the output with regexp (if you are solving a problem with a regexp, you have two problems)
  • all the way through typical downstream tasks (sentiment classification, translation, etc.) up to writing a small pizza order bot with chatGPT backend where basically the whole operation of the bot is described with one long prompt

What I missed

  • examples of few-shot learning, how to best provide examples right there in the prompt to improve downstream performance as compared to the zero-shot setup
  • how to debug such solutions. Debugging a pizza order bot that follows your long-written prompt with instructions sounds close to impossible

Despite the cons, the course is definitely worth 2-3 hours of your time and 0 euro/dollars. I recommend taking a couple of your own tasks (either from pet-projects or real business tasks) and playing with them as you progress through the course.