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AI Development with Qwen 2.5 & Ollama: Build AI Apps Locally
Rating: 4.2 out of 5(161 ratings)
21,559 students

AI Development with Qwen 2.5 & Ollama: Build AI Apps Locally

Build AI-powered applications locally using Qwen 2.5 & Ollama. Learn Python, FastAPI, and real-world AI development (AI)
Created bySchool of AI
Last updated 2/2026
English
English [Auto],

What you'll learn

  • Set up and run Qwen 2.5 on a local machine using Ollama
  • Understand how large language models (LLMs) work
  • Build AI-powered applications using Python and FastAPI
  • Create REST APIs to interact with AI models locally
  • Integrate AI models into web apps using React.js
  • Optimize and fine-tune AI models for better performance
  • Implement local AI solutions without cloud dependencies
  • Use Ollama CLI and Python SDK to manage AI models
  • Deploy AI applications locally and on cloud platforms
  • Explore real-world AI use cases beyond chatbots

Course content

2 sections • 12 lectures • 1h 27m total length

  • Certificate of Completion0:29

    Finish the course on Udemy, download your Udemy certificate, and email it to School of AI at gmail.com; we'll verify your completion and send your official School of AI certificate.

  • What is Qwen 2.5?1:36

    Gwen 2.5, a powerful Alibaba Cloud LLM in the Tongi Qianwen series, enables text understanding, generation, reasoning, and code assistance with multilingual support and local deployment for privacy.

  • Qwen 2.5 vs. Other Models - Llama3, GPT-4, Mistral1:36

    Compare Qwen 2.5 with llama 3, GPT-4, and Mistral, detailing multilingual support, fine-tuning, and efficiency. Qwen 2.5 delivers powerful, efficient, multilingual local AI for chatbots and coding.

  • What is Ollama?1:22

    Explore Ollama, an open source runtime for local deployment and execution of large language models, with a simple command-line interface to pull, run, and manage models like Gwen and Llama.

  • Why Use Ollama?1:02

    Discover why use ollama for local AI development, comparing it with lang chain and OpenAI API, highlighting local running, privacy, speed, and cost savings.

  • How Do Qwen 2.5 & Ollama Work Together?0:41

    Discover how Ollama runs Qwen 2.5 locally, acting as the engine that connects via the Ollama API and delivers results through FastAPI or a chatbot UI.

  • Summary of Deep Dive into Qwen 2.50:33

    Discover how Qwen 2.5 and Ollama enable local AI apps without cloud services; Qwen 2.5 is a high-performance LLM for chat, coding, and automation.

  • Python Quick Start(Just a Refresher)39:29

    Learn Python basics for building AI apps locally, from installing Python and editors to writing scripts, handling variables, input, math, conditionals, loops, lists, and functions, plus a number guessing game.

Requirements

  • Basic Python knowledge (variables, functions, and loops) - If you do not have - we will cover basic Python
  • Familiarity with APIs (REST APIs, JSON data handling)
  • Basic command-line skills (running scripts, installing packages)
  • A computer with macOS, Windows, or Linux (for local AI setup)
  • Internet connection (to download Qwen 2.5 and dependencies)
  • Optional: Basic knowledge of JavaScript/React (for UI development)

Description

Are you ready to build AI-powered applications locally without relying on cloud-based APIs? This hands-on course will teach you how to develop, optimize, and deploy AI applications using Qwen 2.5 and Ollama, two powerful tools for running large language models (LLMs) on your local machine.

With the rise of open-source AI models, developers now have the opportunity to create intelligent applications that process text, generate content, and automate tasks—all while keeping data private and secure. In this course, you’ll learn how to install, configure, and integrate Qwen 2.5 with Ollama, build FastAPI-based AI backends, and develop real-world AI solutions.

Why Learn Qwen 2.5 and Ollama?

Qwen 2.5 is a powerful large language model (LLM) developed by Alibaba Cloud, optimized for natural language processing (NLP), text generation, reasoning, and code assistance. Unlike traditional cloud-based models like GPT-4, Qwen 2.5 can run locally, making it ideal for privacy-sensitive AI applications.

Ollama is an AI model management tool that allows developers to run and deploy LLMs locally with high efficiency and low latency. With Ollama, you can pull models, run them in your applications, and fine-tune them for specific tasks—all without the need for expensive cloud resources.

This course is practical and hands-on, designed to help you apply AI in real-world projects. Whether you want to build AI-powered chat interfaces, document summarizers, code assistants, or intelligent automation tools, this course will equip you with the necessary skills.

Why Take This Course?

- Hands-on AI development with real-world projects
- No reliance on cloud APIs—keep your AI applications private & secure
- Future-proof skills for working with open-source LLMs
- Fast, efficient AI deployment with Ollama’s local execution

By the end of this course, you'll have AI-powered applications running on your machine, a deep understanding of LLMs, and the skills to develop future AI solutions. Are you ready to start building?

Who this course is for:

  • Python developers looking to integrate AI into their projects
  • Software engineers who want to build LLM-based applications
  • AI/ML beginners eager to learn hands-on AI development
  • Full-stack developers wanting to integrate AI with web apps
  • Tech entrepreneurs exploring AI-powered solutions
  • Students & researchers interested in local AI model execution

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