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Advanced100% tuition-freeDuration: 6 months3 Certification preparation

Advanced AI Systems & Cloud Engineering

Built for developers who already ship code. Over six months you work on production AI systems, then cloud GenAI on AWS with MLOps, governance, and private LLMs. Two capstone projects show employers what you can deliver.

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Six months full-time (1,300 teaching units) for experienced developers: 2-week onboarding bridge, then integrated AI systems with RAG, agents, and evaluation, followed by AWS GenAI, MLOps, and private/on-prem LLMs. Two capstones and prep for AWS AI Practitioner and GenAI Developer Professional. Bildungsgutschein funding may apply when approved.

What you'll be able to do

  • Integration and automation under reliability requirements
  • RAG/agents with evaluation, cost control, and monitoring
  • AWS GenAI delivery with security and compliance
  • Private/on-prem LLM literacy (Ollama/vLLM)
  • MLOps/LLMOps and team-ready review practice
  • Prep for AWS AI Practitioner & GenAI Developer Professional

Portfolio proof

  • Systems capstone
  • Advanced cloud GenAI capstone

Curriculum overview

3 modules

Module 12 weeks

Onboarding bridge

Git, API, Docker, and CI/CD readiness

GitHub ActionsDockerFastAPI
Module 2~3 months

AI systems

Integration, RAG, agents, and capstone

n8nLangChainFastAPIvector DB
Module 3~3 months

Cloud GenAI

AWS GenAI, MLOps, governance, and final capstone

AWSOllamavLLMmonitoring

Frequently asked questions

Common questions about this program — funding, format, and outcomes.

Who it's for

Experienced developers and IT professionals with a proven delivery baseline — maintainable application, Git history, APIs, Docker, and deployment evidence — who want to level up for AI systems, cloud GenAI, and MLOps-oriented engineering roles.

No. This is a lateral-entry advanced program. You should already deliver software with Git, APIs, testing, and deployment discipline. It is not a beginner coding pathway.

Yes. The 2-week onboarding bridge includes readiness checks and alignment on API workflows, Git-based delivery, CI/CD hygiene, containerization, and cloud fundamentals before the main six-month program begins.

Curriculum & format

Phase 1 covers AI systems and automation — integration reliability, RAG, agents, evaluation, and operational safeguards. Phase 2 covers cloud and advanced AI engineering — AWS GenAI delivery, MLOps/LLMOps, private/on-prem LLM patterns (Ollama/vLLM), security, compliance, and observability.

Yes. You will deliver an AI systems capstone and an advanced cloud GenAI capstone with deployment evidence, evaluation reports, documentation, and operational narrative suitable for senior junior or mid-transition role applications.

The program includes structured preparation for AWS Certified AI Practitioner and AWS Certified Generative AI Developer – Professional. AWS Machine Learning Engineer – Associate may be offered as an optional stretch path depending on readiness. Exam success is not guaranteed.

The main program runs for 6 months (1,300 teaching units) plus a mandatory 2-week onboarding bridge, delivered as intensive full-time live online learning.

Outcomes & funding

Target roles may include AI systems engineer, integration/automation engineer, GenAI application engineer, cloud AI engineer, or MLOps/LLMOps-oriented junior-to-mid engineering roles — depending on your prior experience and capstone quality.

Participation may be funded by Agentur für Arbeit or Jobcenter if you are eligible and receive a Bildungsgutschein. You will need to make an appointment with your local agency — they decide eligibility individually. We can share course information and help you prepare for that conversation.

The 9-month AI Systems & Automation Developer pathway starts from workplace AI and builds technical depth progressively for career changers. This 6-month program assumes you already code and deploy software, and moves faster into production AI systems and cloud GenAI engineering.