In Building Systems With The ChatGPT API, you will learn how to automate complex workflows using chain calls to a large language model. Unlock new development capabilities and improve your efficiency in this brand new short course.
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You’ll build:
- Chains of prompts that interact with the completions of prior prompts.
- Systems where Python code interacts with both completions and new prompts.
- A customer service chatbot using all the techniques from this course.
You’ll learn how to apply these skills to practical scenarios, including classifying user queries to a chat agent’s response, evaluating user queries for safety, and processing tasks for chain-of-thought, multi-step reasoning.
This one-hour course, taught by Isa Fulford (OpenAI) and Andrew Ng (DeepLearning.AI), builds on the lessons taught in the popular ChatGPT Prompt Engineering for Developers, though it is not a prerequisite. Hands-on examples make each concept easy to understand. Built-in Jupyter notebooks allow you to seamlessly experiment with the code and prompts presented in the course.
What you'll learn
- Efficiently build multi-step systems using large language models.
- Learn to split complex tasks into a pipeline of subtasks using multistage prompts.
- Evaluate your LLM inputs and outputs for safety, accuracy, and relevance.
