
May 28, 2026
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Head Data Science and Machine Learning Engineering
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Run AI projects and become indispensable. The next wave of innovation requires a new type of manager: someone who can seamlessly translate technical AI capabilities into business strategy and ensure regulatory compliance. At neue fische, we offer more than a bootcamp. We provide professional courses and a practice-driven curriculum. Our unique bootcamp prepares you to lead AI transformation projects from conception to implementation. This 20-week program is designed for professionals ready to secure a strategic, high-impact career.
This training combines solid theoretical foundations with practical, real-world experience. We ensure your portfolio reflects the complexity of managing a full-scale AI project.
➡️ Project based learning: You will work on real projects, receive personalized feedback, and master tools and methods that are in high demand in the AI industry.
➡️ A portfolio for success: Your Capstone project, guided by our coaches, will help you build a strong portfolio and application stack.
Career starter: With our career coaching, portfolio advice, and targeted job application support, you will be well-prepared to make a career transition.
Because it’s the ultimate strategic move, putting you at the intersection of complex technology and business decision-making. Leverage your professional experience and communication skills to lead technical teams, moving into a high-influence role that shapes the intersection of AI and business. Gain essential, in-demand knowledge of regulatory requirements such as GDPR and the EU AI Act, a skill critical for every modern AI deployment - and a real difference-maker for your career.
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Enhance your AI project management skills with our hands-on bootcamp.
Learn how to strategically plan, coordinate, and execute AI projects successfully – from the fundamentals of artificial intelligence to real-world applications in business. Gain essential skills to drive impactful, data-driven AI initiatives.
May | 26th May – 19th Oct ‘26 | Full-Time | Remote | English | Secure seat |
|---|---|---|---|---|---|
Jul | 6th Jul – 27th Nov ‘26 | Full-Time | Remote | English | Secure seat |
Aug | 24th Aug – 22nd Jan ‘27 | Full-Time | Remote | English | Secure seat |
Curriculum

This week sets the stage for the bootcamp. Participants get to know the program team, the roadmap, and the "Manual of Me." They set up their technical environments (VSCode, Python) and learn the fundamentals of command-line operations and version control with Git.

Participants transition into technical skills with Python basics and are introduced to the core concepts of AI-Driven Project Management (AIPM) and Agile methodologies.

Students learn to handle data using Pandas, NumPy, and SQL, while also mastering soft skills like stakeholder management and storytelling with data.

Participants apply data cleaning and visualization techniques in a practical project, culminating in a presentation to non-technical stakeholders.

Introduction to core ML concepts including Linear Regression, evaluation metrics, and the business framework of OKRs and KPIs.

Deep dive into classification algorithms (Logistic Regression, KNN, Decision Trees) and Agile product definition via User Stories.

Advanced modeling techniques with Feature Engineering and Ensemble methods, plus understanding software architecture fundamentals from a PM perspective.

Understanding the legal landscape (GDPR, AI Act) and starting the major ML data product project.

Finalizing ML models and learning how to validate product decisions using A/B testing and feasibility analysis.

Introduction to Neural Networks (ANN, CNN) and PM methodologies for estimation and prioritization.

Exploring Natural Language Processing and Prompt Engineering while learning to build strategic AI product roadmaps.

Leveraging Large Language Models for business cases, understanding RAG (Retrieval Augmented Generation), and AI system architecture.

Implementing RAG systems and using "Vibe Coding" to prototype rapidly with AI tools.

Deep dive into Model Context Protocol (MCP) and scoping AI Agent workflows for enterprise.

In der letzten Phase wirst du eine Präsentation von Agentenprojekten sowie die Einführung deines finalen Abschlussprojekts vorstellen.

Validating capstone ideas through discovery, user research, and prototyping before development.

Finalization of the Capstone project and preparation of the final presentation.
Education must be affordable. Check out all the financing options now.

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!
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.
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
A practical project requires careful planning – here's how to proceed:
Use case definition: Choose a real need, e.g., an HR chatbot, sales lead scoring, or automated image analysis.
Stakeholder communication: Explain how you will collect requirements – by phone, survey, or historical data.
Project roadmap: Set time blocks for data acquisition, model training, evaluation, deployment, and reporting – e.g., in Jira or Trello.
Risk management: Identify risks (e.g., bias, data protection, missing data) and plan countermeasures.
Dashboard/demo: Prepare a demo for family members – show how the model works and what organizational impact it has.
Prior knowledge makes many things easier – here's how to build a solid foundation:
Basic understanding of AI/ML: Use free courses (Coursera: ML Foundations, for example) for basic knowledge in regression, classification, and model evaluation.
Project management methods: Learn fresh agile methods (Scrum, e.g., with a product owner, sprints, and retrospectives) via Scrum.org.
Communication skills: Practice stakeholder discussions through role-playing or public speaking exercises – often a plus in everyday project work.
Quick wins: Research and document a small use case example – "Chatbot for inquiries at events." This way, you can bring good examples directly to the course.
This way, you start prepared – your confidence will grow, and you can hit the ground running.
Practical partners are often available – here's how to find them quickly:
Bootcamp collaborations: Many providers bring partner companies to the bootcamp. Ask about topics and selection processes early in onboarding.
LinkedIn outreach: Connect with CMOs, AI teams, and innovation managers; write personally and ask for mini-projects or advice.
Graduate networks: Alumni are often helpful – ask specifically about practical projects or potential clients.
Regional associations: The XING group "AI Munich" or "Data Science Berlin" often post requests for short pilot projects.
University labs: Inquire at universities with AI research groups – students welcome practical contacts.
Tip: At least 2–3 pitches will lead you directly to real-life use cases – ideal for your portfolio and future roles.
Yes, you can start right away – if you prepare your positioning cleverly:
Focus on use cases: Concentrate on a few, clearly defined areas of application such as "AI in customer service," "automated texts," or "internal knowledge bots."
Portfolio projects: Use your final project as a showcase. Document it in a PDF or on a mini landing page with screenshots, flowcharts, and business impact.
Calculate daily rates realistically: As a beginner, you should start at €350–500/day – depending on the use case, tools, and self-confidence.
Industry experience through collaborations: If you don't come from a specific industry, seek out freelance partnerships or contact startups – many need AI project support.
LinkedIn positioning: Target keywords like AI project management for SMEs or AI use case consulting without tech jargon – this will make it easier for recruiters and companies to find you.
💡 Conclusion: Even without 10 years of professional experience, you can establish yourself as a freelance AI project professional – with positioning, references and commitment.
Here are some of the main differences:
Public sector:
Long decision-making processes, data protection is a high priority
Projects often in pilot mode or as feasibility studies
Very documentation-intensive (specifications, committee feedback)
Startups:
Fast, dynamic, little structure – you're often PM, data analyst, and Scrum Master all rolled into one 😅
Experimentation encouraged – risk is part of the culture
Budget decisions are made ad hoc, often without extensive coordination
Corporations:
Clear role allocation, project managers often only responsible for PM tasks
Long lead times – projects are usually planned for >12 months
High standards in stakeholder management, reporting, and budget responsibility
Depending on your style – whether you're more structure-oriented or adventurous – it's worth making a conscious decision when looking for a job!
Absolutely – there are many funding options if you know where to look:
Education voucher (employment agency): Many AI bootcamps are AZAV-certified. Ask your contact at the employment agency about funding via Kursnet and education vouchers.
Education bonus: In some federal states, you can have up to 50% of the course costs covered – provided you work part-time or earn below certain thresholds.
Foundations & funds: Organizations such as the START Foundation or FuturE Foundation specifically support education for people with a migration background.
Regional offerings: North Rhine-Westphalia, Berlin, Hamburg, and Bavaria sometimes offer their own continuing education subsidies for digital skills development.
📌 Tip: Be sure to get free coaching from an educational advisor before booking – many will only support you if you apply for funding before the course starts.