We recommend following the tutorials in order: Build Your First AI Chatbot — Learn the basics of LLM APIs, conversation memory, and streaming Fine-Tune an LLM on Custom Data — Understand how to adapt models to your specific domain Interactive Code Playground — Experiment with all examples and modify

Python 3.10+ installed Basic Python programming knowledge For fine-tuning: GPU with 16GB+ VRAM (or Google Colab free tier) OpenAI API key (optional — all examples work with local Ollama models too) Get the Code git clone https://github.com/datagate-ch/ai-tutorials.git cd ai-tutorials pip install -r

git clone https://github.com/datagate-ch/ai-tutorials.git cd ai-tutorials pip install -r requirements.txt cp .env.example .env # Edit .env with your API keys Coming Soon Build a RAG System with Vector Databases — ChromaDB, Pinecone, and hybrid search Deploy AI Agents to Production — LangGraph, monit

Build a RAG System with Vector Databases — ChromaDB, Pinecone, and hybrid search Deploy AI Agents to Production — LangGraph, monitoring, and scaling Multi-Agent Systems with CrewAI — Role-based agent coordination AI Agent Security — Prompt injection prevention and output validation Questions or sugg

AI Tutorial Series — Hands-On Guides for DataGate.ch

Reviewed: June 4, 2026

Welcome to the DataGate.ch AI Tutorial Series. These hands-on guides walk you through building real AI systems, from your first chatbot to production-ready fine-tuning pipelines. Each tutorial includes complete code examples you can run locally or in Google Colab.

Available Tutorials

🤖

Build Your First AI Chatbot with Python

Create a conversational AI chatbot with memory, streaming responses, and session persistence. Covers LangChain, OpenAI API, Ollama local models, and error handling with retry logic.

Beginner
LangChain
OpenAI
Ollama
~30 min

🎯

Fine-Tune an LLM on Custom Data

Fine-tune Llama 3.2 on your own dataset using LoRA and Unsloth. Covers data preparation, training, evaluation, deployment with vLLM, and uploading to HuggingFace Hub.

Intermediate
Unsloth
LoRA
vLLM
~60 min

💻

Interactive Code Playground

Try all tutorial code examples in your browser. Includes chatbot, RAG pipeline, LoRA training loop, and model evaluation examples. Each example links to a Colab notebook for instant execution.

All Levels
Colab
Examples

Learning Path

We recommend following the tutorials in order:

Build Your First AI Chatbot — Learn the basics of LLM APIs, conversation memory, and streaming
Fine-Tune an LLM on Custom Data — Understand how to adapt models to your specific domain
Interactive Code Playground — Experiment with all examples and modify them for your use case

Prerequisites

Python 3.10+ installed
Basic Python programming knowledge
For fine-tuning: GPU with 16GB+ VRAM (or Google Colab free tier)
OpenAI API key (optional — all examples work with local Ollama models too)

Get the Code

git clone https://github.com/datagate-ch/ai-tutorials.git
cd ai-tutorials
pip install -r requirements.txt
cp .env.example .env
# Edit .env with your API keys

Coming Soon

Build a RAG System with Vector Databases — ChromaDB, Pinecone, and hybrid search
Deploy AI Agents to Production — LangGraph, monitoring, and scaling
Multi-Agent Systems with CrewAI — Role-based agent coordination
AI Agent Security — Prompt injection prevention and output validation

Questions or suggestions? Reach out via the contact page or open an issue on GitHub.

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AI Tutorial Series — Hands-On Guides for DataGate.ch