Notebooks & editor
A JupyterLab-style environment with a code editor, terminal and file browser in the browser.
Your lab, one click, on our GPUs
Every CapabilityNext course runs in a browser workspace we host on GPU infrastructure we own. No installs, no drivers, no cloud console — and it works from a phone, a tablet or a ten-year-old laptop.
What's in the workspace
Everything wired up before you arrive
Open the module, and the environment is already there — nothing to configure, the same setup for every student.
A GPU, attached
Real accelerator access for training and fine-tuning when the material calls for it — no queue, no setup.
Datasets mounted
Course datasets are already in place and versioned — no downloads, no “where do I put this file”.
Libraries pinned
PyTorch, Hugging Face, vector databases and the rest — pinned to versions that work together.
Your files persist
Your work is saved between sessions — pick up exactly where you left off, from any device.
Isolated per learner
Each workspace is your own sandbox. Your code and data aren't shared with the rest of the cohort.
One-Click Deployment
From “open the module” to “GPU ready” in seconds
Open your module
Pick this week's lesson. No downloads, no accounts to wire up.
Week 3 · Retrieval-augmented generation
▶ Launch lab
Click “Launch lab”
We provision a workspace on our GPUs with datasets and libraries pinned.
Provisioning workspace…
Attaching GPU · loading datasets
ready in ~15s
Start building
A notebook opens with everything imported. Same setup for every student, every device.
$ nvidia-smi
GPU 0 · 40GB · available
>>> from capabilitynext import lab ✓
Illustrative — a real walkthrough video will replace this.
Why we own the infrastructure
Not reselling a cloud — running our own
- No per-student cloud accounts. You never touch a billing page or a console with forty options.
- Predictable cost. Your fee covers the compute; there's no metered bill that surprises you mid-course.
- Tuned for teaching. The environment is built for the curriculum, not a generic VM you have to tame.
- Your data stays with us. Coursework and datasets live on our platform, not scattered across personal cloud tenants.
- Same for everyone. One environment spec means a mentor can actually help — no “works on my machine”.
Common questions
About the platform
What GPU do I get?
A shared high-memory accelerator suitable for the training and fine-tuning the courses require. [State the exact GPU class and any per-session limits once finalised.]
Does my work persist between sessions?
Yes — your files and notebooks are saved to your workspace and are there when you come back, on any device.
Can I use the lab after the course ends?
Self-paced enrolments keep access for the stated period. Live-cohort access runs through the programme plus a wind-down window. [Confirm the exact durations.]
My internet isn't fast. Will it work?
The heavy compute runs on our servers, so you're only sending keystrokes and receiving text — it holds up on modest connections. A stable connection matters more than a fast one.
Can I export my projects?
Yes. You can download your code and artifacts to keep in your own portfolio and repositories.
See it for yourself
Book a call and we'll walk you through the workspace and how a typical week runs.
Talk to an advisor