Learn for FREE SHORT COURSE ChatGPT Prompt Engineering for Developers

https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/

Beginner to Advanced

1 Hour

Isa Fulford, Andrew Ng

Free for a limited time

• Learn prompt engineering best practices for application development
• Discover new ways to use LLMs, including how to build your own custom chatbot
• Gain hands-on practice writing and iterating on prompts yourself using the OpenAI API

What you’ll learn in this course

In ChatGPT Prompt Engineering for Developers, you will learn how to use a large language model (LLM) to quickly build new and powerful applications.  Using the OpenAI API, you’ll be able to quickly build capabilities that learn to innovate and create value in ways that were cost-prohibitive, highly technical, or simply impossible before now.

This short course taught by Isa Fulford (OpenAI) and Andrew Ng (DeepLearning.AI) will describe how LLMs work, provide best practices for prompt engineering, and show how LLM APIs can be used in applications for a variety of tasks, including:

• Summarizing (e.g., summarizing user reviews for brevity)
• Inferring (e.g., sentiment classification, topic extraction)
• Transforming text (e.g., translation, spelling & grammar correction)
• Expanding (e.g., automatically writing emails)

In addition, you’ll learn two key principles for writing effective prompts, how to systematically engineer good prompts, and also learn to build a custom chatbot. 

All concepts are illustrated with numerous examples, which you can play with directly in our Jupyter notebook environment to get hands-on experience with prompt engineering. 

In partnership with OpenAI

We are excited to collaborate with OpenAI in offering this course, designed to help developers effectively utilize LLMs. This course reflects the latest understanding of best practices for using prompts for the latest LLM models.

Who should join?

ChatGPT Prompt Engineering for Developers is beginner-friendly. Only a basic understanding of Python is needed. But it is also suitable for advanced machine learning engineers wanting to approach the cutting-edge of prompt engineering and use LLMs.