Course Review: ChatGPT Prompt Engineering for Developers
If you're interested in learning about how to write good prompts for ChatGPT, then Andrew Ng's free course, ChatGPT Prompt Engineering for Developers, is a must-try. In this article, we'll provide a review of this course and discuss what it has to offer.
Course Overview
The ChatGPT Prompt Engineering for Developers course consists of nine lectures, each lasting between 12 to 15 minutes. The course encourages learners to pause and experiment with the examples provided. The Jupyter Notebook is readily accessible in a sidebar, making it easy to code while watching the lectures.
Lecture Overview
Here's a brief overview of the lectures:
- Introduction: The instructors introduce themselves and provide an overview of the course. They discuss the course's content, including best practices, and set expectations for what learners can expect to gain from taking the course.
- Guidelines: The two key principles for effective prompt engineering are covered in this lecture. The lecturer provides tactics to achieve these principles, such as using delimiters, providing structured output formats, and using few-shot prompting.
- Iterative Prompt Development: This lecture emphasizes the importance of iterative prompt development for specific applications. The speaker provides an example of summarizing a fact sheet for a chair and developing a prompt for helping a marketing team create a product description for an online retail website based on the fact sheet.
- Summarizing: This lecture demonstrates how to use large language models for summarizing text and extracting relevant information. The lecturer uses the ChatGPT Web Interface to summarize product reviews and shows how to use a workflow to summarize multiple reviews.
- Inferring: This lecture highlights the benefits of using large language models for inferring tasks, such as sentiment analysis, entity recognition, and topic modeling. The lecturer encourages the audience to experiment with different prompts and variations.
- Transforming: The diverse applications of large language models in transforming text, including translation, spelling, grammar corrections, and format conversions, are explored in this lecture.
- Expanding: This lecture focuses on the use of large language models for expanding short pieces of text and generating personalized content.
- Chatbot: The potential of using large language models like ChatGPT to develop custom chatbots for various applications is showcased in this lecture.
- Conclusion: This lecture provides a brief recap of the key principles covered in the course.
Conclusion
Overall, the ChatGPT Prompt Engineering for Developers course is a practical and insightful guide to improving prompt engineering skills, with plenty of code examples and step-by-step instructions. We highly recommend it to anyone interested in learning about ChatGPT prompt engineering.
