First Look: ChatGPT API for Web Developers

• Integrating AI into Web Applications: Understand how to leverage AI capabilities using the ChatGPT API, enabling you to create intelligent web applications.
• Understanding Large Language Models: Gain foundational knowledge about large language models (LLMs), including the OpenAI API, tokens, and their use in web development.
• Building ChatGPT Plugins: Learn to create plugins for ChatGPT, focusing on enhancing functionality while maintaining robust security practices.
• Developing a ChatGPT Clone: Apply your skills to build a ChatGPT clone, exploring advanced concepts like conversation context, prompt engineering, and the Image API.
• Exploring Advanced AI Features: Dive into advanced topics such as embeddings, fine-tuning, and using the Langchain framework for developing complex AI applications.
• Prioritizing Security: Understand security measures and techniques, including prompt injection prevention, to protect your AI-integrated applications.

In this course, Maximiliano Firtman provides a comprehensive introduction to integrating AI into web applications using the ChatGPT API. You’ll start with the basics of large language models and the OpenAI API, moving through creating ChatGPT plugins and focusing on security. The course guides you through building a ChatGPT clone and exploring advanced topics such as prompt engineering, conversation context, and image generation. By the end of the course, you'll understand how to use embeddings, fine-tuning, and the Langchain framework to enhance your web applications with AI.

• Web developers interested in integrating AI into their applications.
• Developers looking to learn about ChatGPT API and its applications.
• Software engineers aiming to enhance web applications with AI capabilities.
• Anyone interested in exploring AI tools and techniques for web development.

• Basic Web Development Knowledge: Familiarity with JavaScript, HTML, and web development concepts is recommended.
• Interest in AI Technologies: A desire to learn about AI and its applications in web development.

Introduction

Get an overview of the course, including its objectives and prerequisites, along with a brief introduction to the instructor's background.

AI and Web Development

• AI, LLMs & OpenAI: Explore the relationship between AI, large language models, and GPT technology, and their applications in various tasks.
• OpenAI API & Tokens: Learn how to structure prompts, understand token usage, and explore different OpenAI models like GPT-4 and image models.
• AI & Web Development: Discover how GPT can be used in chatbots, plugins, and content APIs for web applications.

Plugins and Security

• Creating Plugins: Learn to create ChatGPT plugins to enhance AI responses, with practical examples of plugin manifests and endpoint descriptions.
• Security & Prompt Injection: Understand security risks and methods to prevent prompt injection and unauthorized access to websites.

ChatGPT Clone

• Project Setup: Set up your development environment and understand the course repository.
• Adding Your API Key: Generate and securely manage your OpenAI API key.
• Chat Completion API: Make API requests to interact with the ChatGPT model and maintain conversation context.

Prompt Engineering

• Prompt Engineering for Developers: Learn techniques for designing prompts that yield desired responses, focusing on consistency, format, and security.
• Basic Prompt Rules: Discover guidelines for writing effective prompts, including examples and input handling.
• Capabilities: Explore ChatGPT’s capabilities, such as summarization, inference, and data transformation.

Advanced Topics

• Modeling Prompt Data: Apply prompt engineering principles to a cooking app, focusing on recipe search and ingredient identification.
• Using the Image API: Implement the Image API to generate images based on text prompts.

Embeddings & Fine Tuning

• Connecting GPT to Data: Explore techniques for training models with smaller datasets and using search results as context.
• Embeddings: Learn how to convert text into numerical data for efficient processing and context integration.
• Langchain: Utilize the Langchain framework to develop LLM applications and continue learning about AI integration.