LLM + Fine-tuning
Run language models, evaluate their outputs, and adapt them to your tasks with fine-tuning, retrieval, and agents.
An independent academy for AI buildersLEARN · BUILD · TOGETHER
Understand
the stack.
Build working AI.
Explore LLMs and fine-tuning, voice and audio, image generation, video generation, music generation, and OCR. Learn through model tests, practical experiments, and workflows you can build on.
Free lessons. Your pace. Real code.
AI INFRA / ACADEMYPRACTICAL AI EDUCATION
to implementation.
01 / What we explore
Language, sound, and vision.
One place to explore AI.
Six areas of learning and experimentation.
Model tests, benchmarks, and practical workflows.
Voice & Audio
Explore speech recognition, text-to-speech, audio understanding, and voice workflows built with consent.
Image Generation
Generate and edit images, compare model outputs, and build repeatable creative workflows with tools such as ComfyUI.
Video Generation
Experiment with text-to-video and image-to-video, motion consistency, and the steps from generation to a usable clip.
Music Generation
Explore music models, original composition, lyrics, and controllable generation with attention to licensing and creative rights.
OCR
Turn scanned pages and images into usable text, extract document structure, and connect the results to practical automation.
These areas guide our research and growing learning library. Explore the published learning paths below; more tutorials will be added over time.
02 / Published learning paths
Pick a problem.
Start building.
Focused guides for the work in front of you.
Start with a topic. Follow it all the way through.
01Start Mastering Claude Code02Start Retrieval Augmented Generation (RAG)03Start LLM Finetuning
DEVELOPER TOOLS
Mastering Claude Code
Make AI part of your workflow.
Set up Claude Code, manage context, and build repeatable workflows with skills, hooks, and MCP.
RETRIEVAL & KNOWLEDGE
Retrieval Augmented Generation (RAG)
Give your model better context.
Understand retrieval-augmented generation, then put the pieces together in a working RAG pipeline.
MODEL CUSTOMIZATION
LLM Finetuning
Adapt a model to your task.
Learn the foundations of fine-tuning and walk through a practical setup with Unsloth Studio.
03 / How we learn
Knowledge earns
its place in practice.
We test AI models, explore benchmarks, and turn practical experiments into tutorials. Our focus includes automation with open-source and proprietary models.
Open the learning library01
Understand the moving parts.
Start with the concepts: what the system does, where the data goes, and why the architecture matters.
02
Work through the implementation.
Follow concrete examples, commands, and code. Connect each decision to the thing you’re building.
03
Make it your own.
Use the lessons as a starting point. Change the inputs, try a different approach, and keep experimenting.
A good place to begin
Your next project
starts with understanding.
Start with Claude Code Prefer retrieval or model training? Browse every path ↗