Adding AI to your JavaScript Web Application with the ChatGPT API

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TIAS subsidised course @ €480 pp!

Course Description

Did you know that you can add the power of AI to your own JavaScript application by utilising the ChatGPT API?

This TIAS subsidised course is designed for JavaScript Developers who want to learn how to add AI features like sentiment analysis and natural language processing to their applications to make them smarter and more interactive. We’ll start with the basics, such as setting up and making simple API requests, and then gradually explore more advanced topics like analysing usernames for inappropriate content, doing sentiment analysis on comments and analysing a log file for suspicious activity. Continuing on we will do more advanced tasks like specifying how the responses will be formatted using structured data and getting our own information into the model through the use of functions. By the end of the course, participants will have a solid understanding of how to leverage the OpenAI models to create smarter and more interactive JavaScript applications.

Who should attend?

This course is for Web Application Developers and will use JavaScript RESTful API calls to interact with the OpenAI API. The course can be customised for various technology stacks including Angular, React, Node.js and ASP.NET. No experience with AI is assumed. Access to the OpenAI API is a requirement for this course.

Introduction

Introduction to AI Concepts
Understanding the limitations of AI
Web Application development environment
Understanding a RESTful Web Service
Making a call
Understanding the JSON response

Getting Started

Registering for OpenAI API
Getting API key
API Playground
Hello World API Call in playground

Choosing a model

What models are available
Monitoring Usage
Specifying max_tokens
Checking availability

OpenAI Requests In JavaScript

Install OpenAI dependencies
Making a call
Parts of a call - model, temperature, max_tokens, top_p, frequency_penalty, presence_penalty
API Response
Parsing a response

Some Practical Examples

Vetting usernames
Sentiment analysis of comments
Scanning a server log file for suspicious activity

Structured Outputs

JSON mode
Adding a response_format
Utilising responses

API Functions

Providing your information to the API using functions
Providing a function description
Understanding the "function" response
Calling the function
Getting a response
Simple example

More on API Functions

Providing more than one function
Describing multiple functions to assist API in choosing which one to call
More complex example

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