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DeepLearning.AI

Building Systems with the ChatGPT API

  • up to 1 hour
  • Beginner

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.

  • Prompt engineering
  • Large language models
  • Workflow automation
  • Chain-of-thought reasoning
  • Safety evaluation

Overview

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.

  • Web Streamline Icon: https://streamlinehq.com
    Online
    course location
  • Layers 1 Streamline Icon: https://streamlinehq.com
    English
    course language
  • Self-paced
    course format
  • Live classes
    delivered online

Who is this course for?

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.

Pre-Requisites

1 / 1

  • Basic understanding of Python

What will you learn?

Introduction to Building Systems with the ChatGPT API
Overview of the course and its objectives.
Automating Complex Workflows
Learn how to automate complex workflows using chain calls to a large language model.
Building Chains of Prompts
Create chains of prompts that interact with the completions of prior prompts.
Integrating Python Code
Develop systems where Python code interacts with both completions and new prompts.
Customer Service Chatbot
Build a customer service chatbot using all the techniques from this course.
Evaluating User Queries
Classify user queries to a chat agent’s response and evaluate them for safety, accuracy, and relevance.
Chain-of-Thought Reasoning
Process tasks for chain-of-thought, multi-step reasoning.
Hands-on Examples
Experiment with the code and prompts presented in the course using built-in Jupyter notebooks.

Meet your instructors

  • 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.

Upcoming cohorts

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