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Developing AI Systems with the OpenAI API

Leverage the OpenAI API to get your AI applications ready for production.

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Course Description

Get your AI applications ready for production with this OpenAI API course. You’ll discover best practices for developing applications on the OpenAI API, including moderation and validation, testing, and practices for improved safety. You’ll also learn how to connect your application with external systems and APIs through function calling. This course builds on core OpenAI functionalities introduced in Working with the OpenAI API and prompt writing best practices from ChatGPT Prompt Engineering for Developers to help you elevate your projects from proof of concept to production-ready systems.
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In the following Tracks

Associate AI Engineer for Developers

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Developing AI Applications

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OpenAI Fundamentals

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  1. 1

    Structuring End-to-End Applications

    Free

    Learn how to seamlessly incorporate the OpenAI API into more complex systems, mastering the art of manipulating the response format and adeptly handling errors. This chapter provides essential knowledge for those looking to build components of AI systems that are not just interactive but also robust and efficient.

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    Structuring an API call
    50 xp
    Decoding the response
    50 xp
    Formatting model response as JSON
    100 xp
    Handling errors
    50 xp
    Interpreting error messages
    100 xp
    Handling exceptions
    100 xp
    Batching
    50 xp
    Avoiding rate limits with retry
    100 xp
    Batching messages
    100 xp
    Setting token limits
    100 xp
  2. 2

    Function Calling

    Dive into the mechanics of function calling, where you'll master defining parameters to call specific functions, extracting structured data, and working with multiple functions. Learn to seamlessly integrate external APIs and manipulate responses to communicate with other systems, to develop enhanced AI system interactions.

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    Defining function calling
    50 xp
    Function calling definition
    50 xp
    Function calling steps
    100 xp
    Extracting structured data from text
    50 xp
    Using the tools parameter
    100 xp
    Building a function dictionary
    100 xp
    Extracting the response
    100 xp
    Working with multiple functions
    50 xp
    Parallel function calling
    100 xp
    Setting a specific function
    100 xp
    Avoiding inconsistent responses
    100 xp
    Calling external APIs
    50 xp
    Defining a function with external APIs
    100 xp
    Calling an external API
    100 xp
    Handling the response with external API calls
    100 xp
  3. 3

    Best Practices for Production Applications

    Elevate your OpenAI API skills to follow the industry's best practices. Learn to moderate content with precision, validate model behavior for consistency, and implement safety measures for secure API usage. This final chapter is an essential part of building robust AI-powered applications.

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    Moderation
    50 xp
    Mitigating prompt injection
    50 xp
    Moderation API
    100 xp
    Adding guardrails
    100 xp
    Validation
    50 xp
    Potential for model errors
    50 xp
    Adversarial testing
    100 xp
    Safety best practices
    50 xp
    Minimizing model risks
    50 xp
    Including end-user IDs
    100 xp
    Wrap-up
    50 xp
For Business

Training 2 or more people?

Get your team access to the full DataCamp platform, including all the features.

In the following Tracks

Associate AI Engineer for Developers

Go To Track

Developing AI Applications

Go To Track

OpenAI Fundamentals

Go To Track

collaborators

Collaborator's avatar
James Chapman
Collaborator's avatar
Jasmin Ludolf

prerequisites

Python ToolboxChatGPT Prompt Engineering for Developers
Francesca Donadoni HeadshotFrancesca Donadoni

AI Curriculum Manager at DataCamp

Francesca is an AI Curriculum Manager at DataCamp, where she works to create courses, content, and solutions for AI learning. She has a keen interest in inclusive and accessible AI-based technologies. After graduating from Imperial College London in 2014, she earned a master's and PhD in Bioengineering at UCL. She spent two years at Northwell Health Labs in the US developing algorithms with clinical data, then returned to London to work as a Machine Learning and AI Engineer with startups before joining DataCamp.
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