Cloud Computing with AI
Build the cloud backbone AI runs on — an in-demand skill in 4 weeks.
What this course is about
Every AI application is only as good as the infrastructure it runs on. This four-week course takes you behind the model and into the cloud platforms that make AI possible at scale.
You'll learn cloud integration, how to scale AI workloads efficiently, how to work with big data, and how to keep all of it secure. These are the in-demand, future-proof skills that sit at the intersection of cloud and AI — and they travel across every industry.
Your week-by-week journey
Fundamentals of Cloud Computing
Understand the architecture behind AWS and Azure — compute, storage, networking and security. Learn how cloud environments are structured and how AI services integrate at the infrastructure level.
Integrating AI Services into Cloud Platforms
Deploy managed AI services — computer vision, NLP, speech and recommendation engines — without building from scratch. Wire them into real applications using APIs and cloud-native tooling.
Scaling Machine Learning Models in the Cloud
Take a model from your laptop to production. Learn MLOps fundamentals: versioning, CI/CD pipelines for ML, auto-scaling inference endpoints, and monitoring model performance in the wild.
Big Data Processing and Cloud Security
Process large datasets using cloud-native big data tools. Understand shared-responsibility security models, encryption, IAM best practices, and compliance requirements for AI workloads.
What you'll work with
Who benefits from Cloud Computing with AI
Cloud Engineers
Add AI service integration and MLOps to your skill set and take on higher-value infrastructure work.
Data Scientists
Learn to deploy, scale and monitor your models in production cloud environments.
DevOps Engineers
Extend your CI/CD expertise to ML pipelines and AI model lifecycle management.
IT Security Experts
Understand the specific security and compliance requirements AI workloads introduce in the cloud.
What you get
Funding may be available
Eligibility and funding levels are assessed case by case by the responsible public authority. There is no legal entitlement.
Live AWS & Azure Practice
Work inside real cloud environments every session — not local simulations.
AZAV & DEKRA Certified
Graduate with an EU-recognised certificate in cloud AI engineering.
Berlin & Online
Join live online or attend in person at our Berlin campus.
MLOps Included
One of the few courses that covers the full pipeline from model training to production deployment.
Expert-Led Training
Learn from cloud architects and ML engineers who deploy AI at enterprise scale.
What you'll need
It's built for you if…
How to join — 3 simple steps
Free consultation
Book a 30-minute call. We check if you qualify for funding — no obligation.
We handle the paperwork
We guide you through the Bildungsgutschein or QCG application, step by step.
Start after approval
Choose a confirmed date after the responsible authority has reviewed any funding application.
By the end, you'll be able to…
Roles you'll be ready for
Cloud AI Engineer
Design and deploy AI-powered services on AWS and Azure for production workloads.
MLOps Specialist
Build and maintain the pipelines that take ML models from experiment to live deployment.
Cloud Solutions Architect
Design scalable, secure cloud architectures that incorporate AI as a first-class service.
AI Infrastructure Consultant
Help organisations migrate AI workloads to the cloud and optimise for cost and performance.
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