Studying
GPU Lab — your AI laboratory in the cloud
Train models, build and run AI agents and get your hands on real GPU power — from a single graphics card to an entire cluster. No installations, no expensive hardware at home. Open your browser and get started.
Built on top-tier infrastructure
What is GPU Lab
Real power you would not normally get your hands on
GPU Lab is a cloud environment with NVIDIA graphics cards that we make available to our students — primarily in our artificial intelligence courses. Instead of dealing with expensive hardware, drivers and configuration, you get a ready-made environment where you can immediately train models, experiment with LLMs and build and run AI agents.
It is not just a single GPU instance
In selected courses you get access to an entire GPU Kubernetes cluster — not just one card for experiments, but real, scalable infrastructure of the kind used to deploy and run AI services in companies. It is the same type of environment that real AI products run on — so you get to know practice as it really looks.
Architecture diagram: workloads (training, inference, notebooks) run through the Kubernetes control plane on GPU worker nodes with NVIDIA GPUs, with shared monitoring and persistent storage.
Why GPU Lab
Why we put GPUs in our students' hands
Practice from the first lesson
You cannot learn AI from theory alone. You need something to train on and something to run — with us you have it available right away.
No barrier to entry
A powerful GPU costs thousands of euros. We provide it, and you focus on learning instead of buying expensive hardware.
A real environment, not a toy
In selected courses you get not just a single GPU instance but access to an entire GPU cluster — you work with the tools and practices companies actually use: containers, Kubernetes and monitoring.
A path to certification
The environment is set up so that you can also prepare for NVIDIA’s AI agent certification in it — on real infrastructure, not just in theory.
Possibilities
What you can do in GPU Lab
From your first experiments to running agents on a cluster — all in one place and with real GPU power.
Model training and fine-tuning
Train neural networks and fine-tune language models on your own data with full GPU acceleration.
AI agent development
Build agents on top of LLMs and connect them to tools (tool calling), memory and vector databases.
Operation, testing and inference
Let agents run in real time, test their behaviour and expose a model or agent as an API endpoint.
Jupyter and experiments
Interactive notebooks for rapid prototyping, data analysis and visualisation of results.
Kubernetes cluster and MLOps
Deploy workloads to a GPU Kubernetes cluster, scale services and learn modern MLOps practices.
Monitoring and observability
Track GPU and memory usage, throughput and metrics of models and agents in real time.
Certification
Prepare for the NVIDIA AI Agent certification hands-on
GPU Lab is the ideal training environment for students aiming for NVIDIA’s AI agent certification. Instead of dry memorisation, you try everything out on real NVIDIA infrastructure.
- You build agentic applications on top of LLMs — exactly as the certification requires.
- You work with GPU acceleration, containers and cluster deployment.
- You test and run agents end-to-end — from prototype to inference endpoint.
- It ties in with our AI courses, where we guide you through the whole process.
Benefits for you
What GPU Lab saves you
- No installation or configuration — the environment is pre-configured (CUDA, libraries, tools).
- No hardware costs — you do not have to buy or rent expensive GPUs.
- You learn on what is actually used — the same tools as in companies.
- Faster progress — you do not waste time on technical problems, you focus on AI.
- Safe experimentation — you can try, fail and repeat without risk.
Join us
Get your hands on real AI
GPU Lab is part of our AI courses. Start building and running agents on real infrastructure.