AI Production-Ready Bootcamp
23 November, 2026 – Amsterdam, The Netherlands
Take your machine learning code from notebook to production and your AI coding assistant from autocomplete to something you can direct, check and rely on. Over four intensive days you’ll learn to turn ML projects into high-quality Python packages, serve them through APIs and CLIs, and work deliberately with an AI coding assistant on a real Python codebase, leaving with habits that hold up on code other people depend on.
Looking to upskill your team(s) or organization?
Juanette will gladly help you further with custom training solutions.
Juanette Evans
Data and AI Training Advisor
Duration
4 days
Time
09:00 – 17:00 (GMT +1:00)
Language
English
Lunch
Included
Certification
No
Level
Professional
Two Trainings. One Powerful Bootcamp.
The AI Production-Ready Bootcamp combines two complementary courses, delivered in person over four intensive days in Amsterdam. They’re designed to sit together as a package: Production-Ready Machine Learning teaches you to take a model from a notebook to a tested, installable, running service, and AI-Assisted Coding teaches you to work with an AI assistant on that kind of code without losing control of it. Either course can also be taken on its own.
What will you learn during AI Production-Ready Bootcamp?
yAfter the training, you will be able to:
Build and ship production-ready ML code: explain what it means for a project to be production-ready, write robust Python code that is easy to extend, debug, monitor and test, structure your projects as high-quality Python packages with uv, and serve your models through APIs and CLIs
Make AI assistance repeatable and well-judged: engineer the context an assistant works from, including a project instruction file your whole team can rely on, automate repeated instructions and checks, and judge where AI genuinely speeds up delivery using what the research measures rather than what the vendors claim
Direct and verify an AI coding assistant: explain what it can and cannot see in your project, write prompts that scope the change and define what done means, and review AI-generated code critically before you accept it
Program
The bootcamp combines two courses delivered in person over four intensive days in Amsterdam.
- Explain what it means for a project to be production-ready
- Write robust Python code that is easy to extend, debug, monitor and test
- Structure ML projects as high-quality Python packages with uv
- Serve your models with APIs and CLIs
This training is for you if:
You want to refactor code from notebooks into mature Python packages, using current industry-standard tools
You already use an AI coding assistant on real work and want to move past autocomplete to direct it deliberately
This training is not for you if:
You don’t have basic Python experience, or have never used Git or a shell/terminal before (check out our Python for Data Analysis course first)
You want to build AI agents or LLM applications rather than use an assistant on your own code (see our LLMs or Agentic AI for Developers course instead)
Requirements
Basic Python experience is required, along with familiarity with Git and comfort using a shell/terminal. A laptop you can install software on is needed throughout: Visual Studio Code, Python 3.10 or newer, and an active Claude subscription. Information on software and tooling will be shared before the start date.
Why should I follow this bootcamp?
Practise on real code
Hands-on exercises throughout, all on a working Python project with real bugs in it.
Leave with something you keep
You write a project instruction file and build your own reusable commands and checks, and you take them back to your own repository.
Get an honest picture
We cover what the productivity research actually measures, so you can set realistic expectations with your team instead of quoting a vendor number.
What else
should I know?
After registering for this training, you will receive a confirmation email with practical information. A week before the training, we will ask you about any dietary requirements and share literature if you need to prepare.
See you soon!
Course information
All literature and course materials are included in the price.
Meet the trainers
Cihan Yatbaz
Cihan is a Data Science Educator at Xebia, where he designs and delivers training programs across the full data science landscape, from Python and SQL fundamentals to machine learning and BigQuery. He combines hands-on industry experience with a natural ability to break down complex topics, helping developers and data teams turn technical knowledge into practical skills.
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