Udemy

Build Full-Stack AI-Powered Apps

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  • 416 Students
  • Updated 11/2025
4.5
(25 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
7 Hour(s) 4 Minute(s)
Language
English
Taught by
Mosh Hamedani
Rating
4.5
(25 Ratings)
2 views

Course Overview

Build Full-Stack AI-Powered Apps

Learn how to integrate AI into your apps - no ML background needed

AI is everywhere — but can you actually build with it?

Most developers have played around with ChatGPT. Maybe you’ve even copied some AI-generated code into your project. But that’s not the same as building real, AI-powered features that make your apps smarter, more engaging, and more valuable to users.

That’s exactly what this course is about.

In Build Full-Stack AI-Powered Apps, I’ll walk you step by step through the concepts, modern tools, and best practices you need to create production-ready apps powered by AI.

This is the AI course every developer needs right now.

What You'll Learn

  • Understand Large Language Models (LLMs) and how they work

  • Work with tokens, context windows, and model settings

  • Write effective prompts using proven prompt engineering techniques

  • Build a chatbot from scratch with a clean, maintainable architecture

  • Create a review summarizer that helps users make faster decisions

  • Integrate open-source models using Hugging Face and Ollama

  • Run models locally on your own machine

  • Apply best practices and clean code principles

  • Use modern tools to build full-stack AI-powered apps (Bun, Tailwind CSS, shadcn/ui, Prisma, and more)


What You'll Build

Chatbot: Build a chatbot that can answer questions about an imaginary theme park — things like “What rides are suitable for kids under 10?”, “Where can I find vegetarian food options?”, or “What are the park’s opening hours?”. Instead of clicking through menus or digging through a website, visitors can get instant answers. Step by step, you’ll create the backend, structure your code using clean architecture principles, and build a modern frontend that makes the experience seamless and engaging.

Review Summarizer: These days, lots of apps let users summarize content so they can make faster decisions. In this project, we’ll build a tool that condenses customer reviews into clear, actionable insights. The techniques you’ll learn here can be applied to all sorts of AI-integrated features.

Course Content

  • 8 section(s)
  • 111 lecture(s)
  • Section 1 Getting Started
  • Section 2 Introduction to AI Models
  • Section 3 Setting Up a Modern Full-Stack Project
  • Section 4 Project: Building a ChatBot
  • Section 5 Prompt Engineering
  • Section 6 Project: Building a Review Summarizer
  • Section 7 Building with Open-Source Models
  • Section 8 Course Wrap Up

What You’ll Learn

  • Understand Large Language Models (LLMs) and how they work
  • Work with tokens, context windows, and model settings
  • Write effective prompts using proven prompt engineering techniques
  • Build a chatbot from scratch with a clean, maintainable architecture
  • Create a review summarizer that helps users make faster decisions
  • Integrate open-source models using Hugging Face and Ollama
  • Run models locally on your own machine
  • Apply best practices and clean code principles
  • Use modern tools to build full-stack AI-powered apps (Bun, Tailwind CSS, shadcn/ui, Prisma, and more)


Reviews

  • B
    Barbara Prusiewicz
    1.5

    Too much bun + how to use vscode, etc.

  • U
    Udemy User
    4.5

    SO FAR SO GOOD

  • A
    Amarjit Jha
    2.5

    The course went too deep into building the application layer rather than focusing on the AI aspects. However a good starting point for any developer looking to explore the AI development aspects.

  • R
    Randy Sincoular
    4.5

    So far, so good!

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