Comparing and Using AI APIs

Explore the vast landscape of Artificial Intelligence (AI) Application Programming Interfaces (APIs)

Overview

This course is designed for developers, data scientists, and technology enthusiasts, to equip them with the knowledge and skills necessary to evaluate, select, and implement AI APIs effectively in various projects. 

Through a blend of theoretical insights and practical exercises, attendees will gain hands-on experience with some of the leading AI APIs in the market, understand their unique features, and learn how to integrate them into applications to solve real-world problems. Whether you're looking to enhance your product with AI capabilities, or simply curious about the potential of AI APIs, this course will provide you with a solid foundation and the confidence to navigate the AI API ecosystem.

This course is ideal for anyone looking to build on their working knowledge of large language model AI systems like ChatGPT to leverage the power of AI APIs and enhance their projects or products. Join us to unlock the potential of AI APIs and transform the way you approach problem-solving and innovation.

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Full course details

Course outline

1. Introduction to AI APIs

  • Overview of AI and its applications
  • Understanding APIs in the context of AI
  • Types of AI APIs (e.g., natural language processing, computer vision, machine learning models)

2. Key Players in the AI API Market

  • Overview of leading AI APIs (e.g., OpenAI's GPT, Google Cloud AI, IBM Watson, Microsoft Azure AI)
  • Comparative analysis of features, strengths, and limitations
  • Pricing models and accessibility

3. Evaluating AI APIs for Your Needs

  • Defining project requirements and objectives
  • Criteria for selecting an AI API (e.g., performance, scalability, ease of integration)
  • Legal and ethical considerations

4. Getting Started with AI APIs

  • Setting up developer accounts and API keys
  • Understanding documentation and SDKs
  • Basic operations with AI APIs (e.g., sending requests, handling responses)

5. Integrating AI APIs into Applications

  • Best practices for API integration
  • Handling errors and exceptions
  • Optimizing API usage and managing costs

6. Practical Workshop

  • Guided project: Integrating an AI API into a sample application
  • Troubleshooting and optimization tips

7. Q&A and course wrap-up

Audience / prerequisites

This course assumes a working knowledge of large language model AI systems like ChatGPT and CprimeAI. This includes basic terminology, basic prompt writing, and using such systems via pre-existing web-based interfaces. 

Learners who lack such prior working knowledge should take (prior to Government Use of AI/ML) a course like:

  • ChatGPT Prompt Engineering Primer will provide a working knowledge of large language model AI systems like ChatGPT and CprimeAI. This includes basic terminology, basic prompt writing, and using such systems via pre-existing web-based interfaces. 

In this class you will learn how to

After completing this course, you will be able to:

  • Understand the landscape of AI APIs and their applications
  •  Evaluate and select AI APIs based on project requirements
  •  Integrate AI APIs into applications effectively
  •  Navigate the ethical and legal considerations of using AI APIs
  • Stay informed about the latest trends and advancements in AI APIs

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