- Prompt's Construction Principles Guidelines
- How to iteratively optimize Prompt Itrative
- Text Summary Summarizing
- Text Inferring Inferring
- Text Conversion Transforming
- Text Expansion Expanding
- Chatbot Chatbot
Welcome to the ChatGPT Prompt Engineering for Developers course! This course will teach you how to utilize a large language model (LLM) effectively to create powerful applications. By leveraging the OpenAI API, you can now develop innovative solutions that were previously expensive, technically challenging, or even impossible.
Led by Isa Fulford from OpenAI and Andrew Ng from DeepLearning.AI, this short course provides insights into how LLMs function, offers best practices for prompt engineering, and demonstrates the use of LLM APIs in various applications.
- Understand the working of LLMs
- Master prompt engineering best practices
- Utilize LLM APIs for various tasks:
- 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)
- Learn two key principles for writing effective prompts
- Systematically engineer good prompts
- 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.
Unlock the full potential of ChatGPT and revolutionize your application development process with the ChatGPT Prompt Engineering for Developers course!