01 · Career entry
Internships & AI training
Learn software.Use AI safely.Build real skill.
Two clear paths instead of course overload: a guided start in real software work or compact AI training for your company.
Already invited? Open AcademyInternships & AI training
Choose your starting point
4 weeks · up to 200 learning hours
Path 01 · Career entry
From your first terminal to a real contribution.
You start with an honest placement interview. Then you build real, reusable components step by step – safely and initially without access to our product repositories.
Interview → Setup → Missions → Capstone
Prior knowledge counts. Safety foundations and the capstone remain mandatory.
3 or 5 days
Path 02 · Company teams
AI at work. Safe. Practical.
Your team learns to brief tasks well, handle information appropriately and verify results. Choose a software-independent route or work directly with Atlas.
Four formats · one shared standard
For beginners and intermediate users, with placement before the first workshop day.
Your knowledge counts
No busywork. No guesswork.
You begin with honest questions and a small practical proof. Beginners start at the beginning. Proven experience creates a shorter route.
- 01 10–15 min
Place honestly
Answer questions and solve a small case.
- 02 Adaptive
Get the right route
Known material may be skipped after review.
- 03 Reviewed
Make progress visible
XP and levels motivate. Reviews and real outcomes prove progress.
Four weeks · one visible path
Every week ends with something that works.
This is not a tutorial collection. Every stage combines explanation, independent building, testing, documentation and a short review.
- 01
Workspace & foundations
WSL, terminal, files, Git, web foundations and safe handling of credentials.
setup check + first website - 02
Understand full stack
Frontend, API, database, authentication and failure paths in your own demo application.
working full-stack demo - 03
How we deliver software
Read tickets, plan small changes, write tests, process reviews and control coding agents.
reviewed pull request - 04
Reusable capstone
An independent component with documentation, tests, demo and a clean handover.
portfolio + handover
Four formats · one shared standard
The right depth without skipping safety.
The placement interview sets the depth. A safe start and the final practical case remain mandatory in every route.
Standard
Start safely
Choose tools, brief tasks, verify results and demonstrate one reliable workday workflow.
Build a team routine
Adds role labs, a reusable workflow kit and a measured, reversible team pilot.
Atlas
Work with sources
Connect permissions, source choice, freshness and human decisions in one evidenced result.
Use knowledge as a team
Adds a knowledge lab, an Atlas workflow kit and a jointly reviewed adoption pilot.
Learning becomes useful
Good practice work should save real work later.
Tasks are designed so that a strong result can live on as a template, function or internal blueprint. A separate review always decides whether anything enters a product.
Website template
Multilingual, accessible, tested and clearly documented.
Workflow component
For example an import, report, form or small commerce helper.
Team playbook
Brief, review path, owner, stop rule and measurable value.
Safe practice space first
The start uses synthetic cases, approved accounts and isolated repositories only. Product access is never automatic and requires explicit approval.
Approved learner review · 4/5
A method you can take to real work.
One honest review from the Academy: short, concrete and still in the learner’s own words.
English review
“The n3tz Academy was very practical. I learned how to take a bounded software task from scope through implementation, testing, review and handover, and how to work with an AI agent while checking its output against real evidence. The strongest part was learning to verify the result across different states instead of only checking whether the happy path worked. The main friction came from the Windows/WSL setup, permissions and some acceptance criteria becoming clear only during review. Overall, it gave me a repeatable working method I can apply to real website and application work.”
More approved learner stories will join this rail →
Quick answers
What matters before you start.
Do I need prior knowledge for the four-week entry programme?
No. The programme can start with WSL, terminal, files and web foundations. The interview records prior knowledge and may shorten individual stages.
Do I get immediate access to n3tz product repositories?
No. The entry route uses synthetic data and isolated practice repositories. Later access requires a passed review and explicit approval.
What is the difference between Standard and Atlas?
Standard works with approved AI assistants independently of n3tz software. Atlas adds governed sources, permissions, freshness and shared company knowledge.
Are the workshops suitable for non-technical teams?
Yes. Language, exercises and placement are designed for non-technical beginners and mixed teams. Intermediate participants receive harder proof tasks instead of repetition.
Do we work with real company data?
Not in the exercises. Workshop cases are synthetic. Approved tools, data classes and responsibilities are clarified first.
Can I ask for help?
Yes. The protected Academy combines concise in-product help with mission reviews and coach feedback. The current entry experience is text-based.
Ready to start?