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Choose Your Entry Point. Own Your Outcome.
Our curriculum is built in distinct modules, allowing you to enter and exit based on your current expertise and career goals. Select the specific track that matches your experience level:
1. The Full AI Engineer Track (8 months): Our comprehensive flagship program. This is the complete end-to-end journey for those committed to mastering both the data foundations and advanced engineering in one continuous enrollment.
2. The AI & MLE Bridge (4 months): Designed for active Data Scientists. Skip the fundamentals and jump straight into advanced Machine Learning and deployment.
3. The Data Science & AI Core (4 months): Perfect for beginners. This standalone course covers the essential first half of the route, taking you from zero to a data-ready professional.
Course Content
All content at a glance
Keyfacts
- Full-Time: 16 weeks (Mo – Fr, 09:00 am – 6:30 pm)
- Participants: approx. 15
- Locations: Remote (live online)
- Coaches: 2 per bootcamp
- Course language: English
- Completion: Machine Learning Engineering Certificate
- Future job: Machine Learning Engineer
- Expected salary: 62.000€ - 90.000€
- 100% financing: for unemployed & job seekers
- You'll get a Claude Pro subscription during the bootcamp
Our coaches

Head Data Science and Machine Learning Engineering
Tech Stack
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Become a Machine Learning Engineer – at the neue fische bootcamp
Stop building models that never leave your notebook. Start engineering production-ready systems that scale. The industry is shifting from pure experimentation to operational excellence, and companies need engineers who can bridge the gap between a prototype and a live, reliable service. At neue fische, we provide a deep-dive program that transitions you from data science basics to advanced MLOps, CI/CD for ML, and high-performance model serving.
Hands-On Training for a Scalable Career
At neue fische, we offer more than a bootcamp. We provide professional courses and a practice-driven curriculum. This program balances rigorous engineering principles with the latest ML frameworks, ensuring you are ready to take on the role of a “Builder” in any tech team. You will master the ecosystem that keeps modern AI running.
Why Machine Learning Engineering?
Master the “Ops” in MLOps for Maximum Impact. While many can train a model, very few can maintain it at scale. This program is a strategic investment in the most high-demand niche of the data world. If you come from a Data Science background, you will learn to write clean, production-grade code. If you come from Software Engineering, you will gain the statistical intuition to manage non-deterministic systems. You will emerge as a hybrid expert, ready to lead the deployment of the next generation of intelligent software.
Our partner companies
Starting dates
The next dates: AI & Machine Learning Engineering Bootcamp
✅ The AI & Machine Learning Engineering programme will be fully remote.
Aug | 31st Aug – 8th Jan ‘27 | Full-Time | Remote | English | Secure seat |
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Curriculum
This is what you learn in our AI & MLE Bootcamp
In the first phase students will become familiar with software engineering practices and how they relate to data science. The objective of the first week is to write better code when working with data science projects.
In order to achieve this we will cover software engineering in Python (writing programs, working with git and object-oriented programming). Then we will show how to bridge the gap between the usual data science workflow and production-ready code.
At the end of this phase students will be comfortable with getting data for their models from many different sources in different formats. Data engineering is about moving and transforming data from one place to another in a reliable and trustworthy way. Students will get introduced to data architecture design for batch and real-time data processing. They will learn how to get data from various sources like database access and APIs. They will then learn the concepts of data modeling with dbt. Following that they will build data pipelines with Prefect and learn the concepts of batch processing and streaming. Finally, they will set up a feature engineering pipeline in the cloud for their Data science project.
In the third phase of the bootcamp the students will get familiar with the machine learning lifecycle and how to bring data science products to production. There will be an introductory session on machine learning basics followed by sessions on testing, deployment strategies, and containerization.
In this phase of the bootcamp students will get familiar with what it means to have machine learning products in production working reliably over time. In the previous phase, they learned how to deploy models; now they will learn how to monitor and maintain them.
By the end of this phase , students will be able to understand, build, evaluate AI systems using modern Large Language Model (LLM) technologies. They will develop foundational knowledge of LLM architectures, embeddings, vector search, and prompt engineering; gain hands-on experience constructing Retrieval-Augmented Generation (RAG) pipelines; perform fine-tuning and evaluation of small models; and design custom agentic systems using frameworks such as LangChain, pydanticAI, and MCP.
In this phase, students will learn to deploy and manage LLM applications. They will build FastAPI services, containerize them with Docker, and deploy AI systems to Google Cloud Run. Students will integrate monitoring and observability to ensure reliability, and they will learn to deploy complete RAG and agent pipelines end-to-end.
In the final phase of the bootcamp, students will take on a comprehensive capstone project that brings together everything they’ve learned. They’ll design, build, deploy, and monitor a complete machine learning system that solves a real-world problem. Working in teams, students will operate as a professional MLE group, using best practices from software engineering, data engineering, machine learning engineering, model monitoring, and LLM development. The bootcamp concludes with a presentation and live demo of their solution to instructors and peers.
Simple and affordable
Education must be affordable. Check out all the financing options now.
Education must be affordable. And for everyone. That's why we offer three ways how you can finance your bootcamp with us, guaranteed and very easy.

These steps are important to take the course
Register as a jobseeker early
In order to receive your education voucher for your retraining from the employment agency, the Jobcenter or the Labour Office, you should register as a jobseeker at an early stage. It is therefore very important that you first make an appointment with the relevant office. It's best to do it now!
Get your educational offer from us
The next step on the way to your IT training voucher is quick and easy: Contact us! We will create an official training offer for you that you can then submit to the employment agency, the Jobcenter or the employment office.
Apply for the training voucher
Now it's down to the nitty-gritty: With the training offer we have created, you now go back to your responsible office and apply for your training voucher. As soon as it is approved, you can start your new career with us. We look forward to seeing you!
FAQ
Really good questions, helpful answers
This AI & Machine Learning Engineering Bootcamp is designed for Data Engineers, Data Scientists, and Software Engineers who want to accelerate their transition into Machine Learning Engineering or AI Engineering.
No advanced experience in AI is required to join the bootcamp. However, coding knowledge is necessary to keep up with the course and work on the projects.
After successfully completing the bootcamp, you will be able to develop, train, and deploy machine learning models, generative AI, and AI systems. You will gain hands-on experience with tools and technologies such as Python, SQL, TensorFlow, Docker, and MLOps frameworks, as well as agentic coding tools like Claude Code and GitHub Copilot.
Throughout the program, you will complete 4 mini projects, 3 medium projects, and a final capstone project, giving you multiple opportunities to gain marketable experience.
Graduates of the bootcamp can pursue several in-demand roles in the AI and data industry. Typical career paths include: Machine Learning Engineer, AI Engineer.These roles exist across many industries such as finance, healthcare, e-commerce, and technology. With the skills gained during the bootcamp and the portfolio you build, you will be well prepared to start your career in the growing AI job market.
The application process is simple. First, you contact our admissions team to receive detailed information about the bootcamp as well as an individual training offer. If you plan to finance the program through an education voucher (Bildungsgutschein), you can submit this offer to the Employment Agency or Jobcenter.
Once your voucher or another form of funding has been approved, you can secure your place in the bootcamp and begin your training. Our team supports you throughout the entire process and is available to assist with any questions.

What are you waiting for?
Our Student Admissions team is happy to talk with you, answer your questions, and advise you. Get in touch with us!






