AI Privacy
Local models and open source tools.
Use local AI models to protect your code and comply with privacy regulations.
Prerequisites
- Proficient Python skills
Learning Outcomes
- Local model running
- LLM models for privacy
- IDEs and extension integrations
- Fine-tuning models
Curriculum
Module 1: Local LLM running
- Install and configure runners
- Download models
- Run locally
Module 2: IDE and extensions
- Connect to your IDE
- Extensions for privacy
- Fine-tuning models
Tools we will use
During this course we will use the following tools:
1 - Ollama
2 - Google Gemma LLM
3 - Continue IDE
4 - Aider Chat
Example of a real project
As a demo, we will build a real deployable project.
AgentLib
A documentation scrapper that can be used to feed your LLM models.
Who Should Take This Course
This course is perfect for:
- Software developers seeking to protect their code
- Companies in the need to comply with privacy regulations
- Enthusiasts wanting to get the most of their machines.