DeepLearning.AI
Beginner1h40m

ChatGPT Prompt Engineering for Developers

Instructors: Isa Fulford, Andrew Ng

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Earn an accomplishment with PRO · Updated Oct 6, 2026

  • Beginner
  • 1h40m
  • 9 Video Lessons
  • 7 Code Examples
  • 1 Graded Assignment PRO
  • Earn an accomplishment with PRO
  • Updated Oct 6, 2026
  • Instructors: Isa Fulford, Andrew Ng
  • OpenAIOpenAI
  • Learn more aboutMembership PRO Plan

What you'll learn

  • 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

Course recap

PRO

This foundational course, taught by Andrew Ng and Isa Fulford (OpenAI), covers prompt engineering best practices for developers using the ChatGPT API. It distinguishes between using LLMs conversationally (ChatGPT web UI) and programmatically (API calls for building software applications), focusing on the latter as an underappreciated developer tool.

Concept map

Concepts in ChatGPT Prompt Engineering for Developers and the courses that connect to themChatGPT Prompt Engineering for DevelopersChatGPT Prompt Engineerin…Prompt EngineeringBase LLM vs instruction-tuned LLMBase LLM vs instruction-t…Reinforcement learningClear and specific instructionsClear and specific instru…Give the model time to thinkGive the model time to th…Building Systems with the ChatGPT APIBuilding Systems with the…Building Toward Computer Use with AnthropicBuilding Toward Computer…Building with Llama 4AI Agents for Image and Video GenerationAI Agents for Image and V…Building AI Browser AgentsConcepts in ChatGPT Prompt Engineering for Developers and the courses that connect to themChatGPT Prompt Engineering for DevelopersChatGPT Prompt…Prompt EngineeringPrompt Engineer…Base LLM vs instruction-tuned LLMBase LLM vs ins…Reinforcement learningReinforcement l…Clear and specific instructionsClear and speci…Give the model time to thinkGive the model…

Key concepts

  • Prompt EngineeringSystematic techniques for crafting effective prompts for instruction-tuned LLMs
  • Base LLM vs instruction-tuned LLMBase LLMs predict next words; instruction-tuned LLMs follow instructions via fine-tuning and RLHF
  • Reinforcement learningRLHF (Reinforcement Learning from Human Feedback) used to make instruction-tuned LLMs more helpful and safe
  • Clear and specific instructionsFirst principle of prompting: specify tone, format, length, and focus
  • Give the model time to thinkSecond principle: prompt the model to reason step by step before concluding

Lesson highlights

  1. 1.Introduction — LLM types, prompting principles, and course overview
  2. 2.Guidelines — Two principles of prompting (clarity and giving time to think)
  3. 3.Iterative — Iterative prompt development process
  4. 4.Summarizing — Summarization use cases
  5. 5.Inferring — Sentiment analysis and information extraction
  6. 6.Transforming — Translation, tone adjustment, format conversion
  7. 7.Expanding — Generating longer content from short prompts
  8. 8.Chatbot — Building a conversational chatbot
  9. 9.Conclusion — Key takeaways

About 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.

Course Outline

9 Lessons・7 Code Examples
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Instructors

Isa Fulford

Isa Fulford

Member of Technical Staff, OpenAI

Andrew Ng

Andrew Ng

Founder, DeepLearning.AI; Co-founder, Coursera

Generative AI offers many opportunities for AI engineers to build, in minutes or hours, powerful applications that previously would have taken days or weeks. I’m excited about sharing these best practices to enable many more people to take advantage of these revolutionary new capabilities.

– Andrew Ng

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