
Nov 20, 2025
Are you ready to get started in the world of IT? Find out all about financing bootcamps in our info session on education vouchers.
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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, our unique bootcamp prepares you to lead AI transformation projects from conception to implementation. This 18-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.
Jan | 26th Jan – 8th Jun ‘26 | Full-Time | Remote | English | Secure seat |
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Curriculum
Start with a solid introduction to the bootcamp, learn effective learning strategies, and lay the foundation for a career in AI project management. You'll set up your technical setup, learn Git workflows, and delve into Python basics, Pandas, and Numpy.
Work with Pandas and SQL to extract, clean, and prepare data for analysis. Learn how to visualize data meaningfully to gain business-relevant insights.
Deepen your understanding through an EDA project using real data sets. Present your results to stakeholders, learn basic machine learning concepts, and gain a first insight into project management planning.
Build a solid foundation in supervised learning techniques – from regression and classification to model evaluation and regularization, decision trees, ensemble methods (bagging and boosting), and hyperparameter tuning. Apply your knowledge in practical ML challenges.
Learn the ins and outs of AI project management. Use Jira and Confluence for planning and documentation, create user stories and PRDs, and implement Agile Scrum methods with all relevant ceremonies.
Dive deeper into deep learning architectures—from artificial neural networks to convolutional neural networks. Work with transfer learning and NLP, learn about RAG models, agents, and prompt engineering, and understand the importance of data protection in AI projects.
Learn the entire model deployment process: from A/B testing to Docker containers and APIs to deployments on Google Cloud. Learn how to monitor, test, and optimize models for scalability in production.
Understand how AI projects are evaluated and implemented in a corporate context. Work on risk analyses, feasibility studies, effort estimates, and KPIs. Learn about Green IT practices, GDPR/AI Act compliance, and stakeholder management.
Start your final project by tackling a real-world business problem with an AI solution—including design thinking, data manipulation, model training, cloud deployment, and compliance aspects. Your capstone project showcases your entire bootcamp journey.
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.
Tool know-how: Familiarize yourself with Jira, Confluence, and Mural – many bootcamps use them in a practical way.
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.