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Course Description
Building AI applications has never been more accessible with the Responses API! In this course, you’ll learn how to prompt models through a simple interface, follow best practices for reasoning models, and design natural back-and-forth conversations with LLMs. You’ll unlock the full power of LLMs by integrating tools—like web search with no extra API keys or credentials—and by building your own to extend model capabilities beyond their base knowledge. You’ll also learn how to take your applications from prototype to production with three key design paradigms, generate reliable structured outputs like JSON, stream real-time semantic events for interactive user experiences, and go multi-modal by combining text and images using OpenAI’s GPT-5 models.
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Getting Started with the Responses API
FreeBuilding AI applications has never been easier with the Responses API! Learn how to prompt models using a simple interface, best practices for working with reasoning models, and how to build back-and-forth conversations with LLMs.
The Responses API: a Developer's Best Friend50 xpYour First Responses API Call100 xpAdding Model Instructions100 xpExtracting Information from the Response100 xpMastering Response Parameters50 xpExperimenting with More Powerful Models100 xpReasoning About Reasoning100 xpConversation Chaining50 xpFrom One Message to Another100 xpEnabling Chat Conversations100 xp - 2
Building Tools for LLMs
LLMs are powerful, but they're even more powerful once tools are introduced! Learn how to integrate web search with your LLM systems with no additional API keys or credentials. Discover that tools can be, well... pretty much anything! Build your own tools for LLMs to call to go beyond the model's base capabilities.
Response Items: The Building Blocks50 xpExtracting Output Items and Their Contents100 xpUsing Items for Custom Handling100 xpWeb Search That Just Works50 xpCombining LLMs and Web Search100 xpBuilding Confidence with LLM Sources100 xpFunction-Calling Tools: Defining the Function50 xpThe Function-Calling Tool Workflow100 xpDefining a Function for Converting Timezones100 xpFunction-Calling Tools: The Full Workflow50 xpBuilding the OpenAI Tool Definition100 xpIntegrating Function-Calling Tools100 xp - 3
Advanced Patterns for Production
Move your LLM systems from proof-of-concept to production with three key design paradigms. Learn how to generate consistent and reliable structured outputs, like JSON, using LLMs. You'll also use semantic events to stream updates to your users, creating interactive and enjoyable experiences. Finally, go multi-modal and learn how to combine text and images with OpenAI's GPT-5 models.
Generating Structured Outputs50 xpConsistent Outputs, Every Time!100 xpNesting Pydantic Classes100 xpStreaming with Semantic Events50 xpStreaming OpenAI Responses100 xpStreaming Semantic Events100 xpStreaming with Function Calls100 xpInput Flexibility and Multimodality50 xpRole-Based Inputs100 xpPrompting with Images from URLs100 xpPrompting with Local Image Files100 xpCongratulations!50 xp
Training 2 or more people?
Get your team access to the full DataCamp platform, including all the features.collaborators

prerequisites
Working with the OpenAI APIAI Curriculum Manager, DataCamp
James is a Curriculum Manager at DataCamp, where he collaborates with experts from industry and academia to create courses on AI, data science, and analytics. He has led nine DataCamp courses on diverse topics in Python, R, AI developer tooling, and Google Sheets. He has a Master's degree in Physics and Astronomy from Durham University, where he specialized in high-redshift quasar detection. In his spare time, he enjoys restoring retro toys and electronics.
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