Advanced Self-Hosted AI System

Build, Connect & Automate Your Own Local AI

Take your local AI skills to the next level. In this hands-on Advanced Self-Hosted AI course, you will move beyond simply running AI models and learn how to build AI systems that can use your own knowledge, access tools, perform tasks, and work as agents.

Building on the foundations of Ollama, local AI models, Open WebUI, and AI agents, this course focuses on practical projects and real-world applications.

Course Highlights

• Hands-on practical training
• Learn how to build RAG-based AI systems
• Connect AI models to your own documents and knowledge
• Learn how AI can use external tools
• Build and experiment with AI agents
• Explore MCP and AI tool integration
• Automate practical tasks using AI
• Build your own local AI assistant
• Work with Ollama and Open WebUI
• Beginner-friendly advanced training
• Certificate of Completion

1. AI Tools & Function Calling

Learn how AI can go beyond generating text and actually use tools.

You will explore:

• What AI tool calling is
• How AI interacts with external tools
• Calculator and utility tools
• File and document tools
• Python-based tools
• How an AI decides when to use a tool
• Building simple tool-enabled AI systems

2. AI Agents

Go beyond chatbots and learn how AI agents can perform multi-step tasks.

You will learn:

• How AI agents work
• Agent planning and decision-making
• Using multiple tools
• Agent → Tool → Result workflows
• Building practical AI agents
• Testing and improving agent behaviour
• Creating agents that can perform tasks rather than simply answer questions

3. AI Automation

Learn how AI can become part of automated workflows.

Examples include:

• Automatically analysing documents
• Processing information with AI
• Generating reports
• Classifying information
• Connecting AI with other applications
• Creating multi-step AI workflows

4. Final Project — Build Your Own Local AI Assistant

Put everything together and build a practical self-hosted AI system.

Your project can combine:

Ollama + Local AI Model + Open WebUI + RAG + Tools + Agents + Automation

The goal is to finish the course with a working AI system that you can continue developing after the course.

Practical Projects

During the course, you will work on practical exercises such as:

• Building a private document-based AI assistant
• Creating an AI knowledge base
• Connecting an AI model to tools
• Creating a tool-using AI assistant
• Building a multi-step AI agent
• Exploring MCP integrations
• Creating AI-powered automation
• Building a complete local AI assistant

Who Is This Course For?

This course is ideal for:

• Students who have completed a basic local AI course
• Developers and programmers
• IT professionals
• AI enthusiasts
• Linux users
• Students interested in AI agents and automation
• Anyone who wants to build practical AI systems locally

Recommended Knowledge

Students should have basic familiarity with:

• Linux/Ubuntu
• Command-line/terminal usage
• Ollama
• AI models
• Open WebUI

Previous experience with our Self-Hosted AI From Zero course is recommended.

Course Details

Start Date:  16 October 2026 (Every Friday)

Time: 20:00 – 22:00 UK time

Schedule: 4 Live Online Sessions

Duration: 8 Hours Total (We offer flexible timing)

Level: Advanced / Practical

Format: Live Online Training

Fee: £180

Certificate

Students who complete the course will receive a Certificate of Completion.

What You Will Leave With

After completing the course, you will have:

• A practical understanding of modern AI
• Experience working with AI models
• Ollama installed and configured
• At least one AI model running locally
• Experience managing local AI models
• An understanding of AI agents
• Practical experience configuring Hermes
• Your own basic self-hosted AI environment
• A foundation for learning more advanced AI, automation and agent systems
• Certificate of Completion

What You Will Build

By the end of the course, you won't just understand AI agents—you will have experience building and connecting a local AI system.

You'll move from:

"I can run an AI model."

to:

"I can build an AI system that can access knowledge, use tools, perform tasks and automate workflows."