Run AI Locally with Gemma and Ollama: Build Your First App
38mBeginner2026-06-23
Authors

Laurence Moroney
Course details
Learn how to run AI models locally using Ollama and Gemma 4, eliminating reliance on cloud services while maintaining privacy and control. Set up and configure a local model, explore prompting and parameter tuning, and customize behavior with Modelfiles. Then integrate your model with APIs and build a real-time chat interface for a functional AI application.
This hands-on course is designed for developers, engineers, and technical builders interested in running AI locally. By the end, you have a working local AI app and the skills to extend it further.
Learning objectives
Install and run a local AI model using Ollama on your own machine.
Control a Gemma 4 model using prompts, parameters, and session context.
Customize model behavior with Modelfiles to create tailored AI assistants.
Build a working AI application using local APIs and Python.
Extend a local AI system with a simple UI and real-time interaction.
This hands-on course is designed for developers, engineers, and technical builders interested in running AI locally. By the end, you have a working local AI app and the skills to extend it further.
Learning objectives
Install and run a local AI model using Ollama on your own machine.
Control a Gemma 4 model using prompts, parameters, and session context.
Customize model behavior with Modelfiles to create tailored AI assistants.
Build a working AI application using local APIs and Python.
Extend a local AI system with a simple UI and real-time interaction.
Concepts
Build Local AI Apps with Gemma 4 and Ollama
- Local AI with Gemma 4 - What you ll build and why it matters
- Install Ollama and run Gemma 4 locally
- Chat with Gemma 4 in the Terminal
- Customize Gemma 4 with modelfiles
- Use the Ollama API (OpenAI-compatible)
- Build a Python app with local Gemma 4
- Add a simple Chat UI with Gradio