DeepLearning.AI
In this short course, you will learn to efficiently build multi-step systems using large language models. The course covers how to split complex tasks into a pipeline of subtasks using multistage prompts and evaluate LLM inputs and outputs for safety, accuracy, and relevance.
In Building Systems with the ChatGPT API, you will learn how to automate complex workflows using chain calls to a large language model. You will build chains of prompts that interact with the completions of prior prompts, systems where Python code interacts with both completions and new prompts, and a customer service chatbot using all the techniques from this course. This course is beginner-friendly and includes hands-on examples with built-in Jupyter notebooks for seamless experimentation.
Beginners
Individuals with a basic understanding of Python who want to learn how to build systems using the ChatGPT API.
Intermediate Machine Learning Engineers
Engineers looking to enhance their skills in prompt engineering and large language models.
Advanced Machine Learning Engineers
Professionals seeking to learn cutting-edge techniques for automating complex workflows using large language models.
This course will teach you how to efficiently build multi-step systems using large language models, covering key skills such as prompt engineering and workflow automation. It is ideal for beginners and machine learning engineers looking to enhance their skills and advance their careers.
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Basic understanding of Python
Isa Fulford
Instructor, DeepLearning.AI
Isa Fulford is a member of the technical staff at OpenAI. She is also an instructor at DeepLearning.AI, where she helps others learn about artificial intelligence and machine learning.
Andrew Ng
Founder, DeepLearning.AI
Andrew Ng is the founder of DeepLearning.AI, a Managing General Partner of AI Fund, and the founder and CEO of Landing AI.
Cost
Free
Duration
Dates
Location