Openai Api Mastery: Build Ai Apps With Typescript

Posted By: ELK1nG

Openai Api Mastery: Build Ai Apps With Typescript
Last updated 8/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.00 GB | Duration: 2h 0m

Build real AI apps from scratch - ChatGPT clone, RAG chatbot, email classifier & more with OpenAI's TypeScript SDK

What you'll learn

Connect to OpenAI APIs using TypeScript and Node.js to build real AI-powered applications from basic responses to advanced function calling

Build a terminal ChatGPT clone with real-time streaming responses that works exactly like the ChatGPT interface you already know and use

Create RAG applications that let users chat with custom documents and data files, dramatically improving AI usefulness for specific domains

Implement function calling to let AI trigger real actions in your apps - users describe what they want in plain language, AI executes the code

Requirements

Basic TypeScript knowledge

Description

Most developers think AI integration is complicated. It's not. You just need to know how to connect to the right APIs.In this hands-on course, you'll build multiple working AI applications using TypeScript, Node.js, and the OpenAI API. No theory lectures - just real code you can use immediately.What You'll Build:Terminal ChatGPT Clone - Stream AI responses in real-time, just like the real thingEmail Classifier - Analyze sentiment and return structured JSON data for your appsRAG Knowledge Chat - Let users chat with your custom documents and data filesFunction Calling App - AI that can trigger real actions in your applicationPlus foundational examples - Basic responses, streaming, and structured outputWhat Makes This Different:I've taught almost 80,000 developers on Udemy. I don't waste your time with endless theory or marketing fluff. You'll see working code from minute one.Each example builds practical skills you can apply immediately. The entire development and testing for this course cost me 22 cents in API calls - so you're not looking at expensive experimentation.What You Need:Basic TypeScript knowledgeNode.js installedOpenAI API account (I'll show you how to set this up)That's itWhat You Get:Multiple complete, working AI applicationsAll source code included with every lessonStep-by-step setup and implementationReal-world patterns you can use in any TypeScript projectWhy TypeScript?Because it works everywhere - Next.js, React, Node.js backends, whatever you're building. Learn once, use everywhere.No previous AI experience required. Just bring your TypeScript skills and let's build something useful.Stop wondering how AI integration works. Start building it.

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Need Help? How to Contact Me and Stay in Touch!

Lecture 3 Setting Up Node.js & TypeScript + Your First AI Response

Lecture 4 Streaming AI Responses in Real Time

Lecture 5 Building a ChatGPT Clone from Scratch

Lecture 6 Structured Output: Making AI Return JSON You Can Use

Lecture 7 Tool Calling: Letting AI Trigger Real Actions (Web Search)

Section 2: RAG: AI Chat with Your Knowledge Base

Lecture 8 What is RAG? Concept, Workflow & Project Overview

Lecture 9 RAG Chunking: Fixed-Size as the Baseline

Lecture 10 RAG Chunking: Right-Sized Chunks

Lecture 11 Creating Embeddings from Chunks

Lecture 12 Query Embedding & How to Compare the Query Vector to Knowledge Base Vectors?

Lecture 13 Inserting Relevant Knowledge into the AI Response

Section 3: Tools (Function Calling) - Giving AI Access to Your Application Data & Actions

Lecture 14 How the Function Calling Works and What it Can Be Used For?

Lecture 15 Define the Tools (Available Functions to Call)

Lecture 16 Add Mock Data & Implement the Functions

Lecture 17 Figure Out Which Functions Need Calling & Call Them

Lecture 18 Making Final API Call with Function Call Results

TypeScript/JavaScript developers wanting to add AI to their apps,React, Next.js, Vue developers building AI-powered frontends,Node.js backend developers creating AI APIs,Any developer curious about practical AI integration without theory overload