Cloud & Infrastructure · 4 Weeks

Cloud Computing with AI

Build the cloud backbone AI runs on — an in-demand skill in 4 weeks.

4.9/5 · 6,300+ graduates trained
Next starts15 Jun'2614 Sep'2616 Nov'26
Cloud Computing with AI
Next start
June 15, 2026
Duration
4 weeks
Format
Berlin | Online
Certificate
Yes — AZAV
Overview

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.

Curriculum · 4 weeks

Your week-by-week journey

01

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.

AWSAzureCloud architectureIaaS / PaaS / SaaS
02

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.

AWS SageMakerAzure AIAPI integrationML services
03

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.

MLOpsCI/CDModel servingAuto-scaling
04

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.

Big DataCloud securityIAMCompliance
Tools & Technologies

What you'll work with

AWSAzureCloud ML ServicesBig Data Tools
Who it's for

Built for green-tech careers

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.

Why this course

What you get

100% Funded

Eligible participants pay nothing — covered by an education voucher or QCG subsidy.

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.

Requirements

What you'll need

PC skills
German (English)
Upcoming start dates

Pick the cohort that fits you

Small groups · limited seats per cohort
15
Jun
15 Jun – 11 Jul 2026
Berlin | Online
Filling fast
14
Sep
14 Sep – 10 Oct 2026
Berlin | Online
Open
16
Nov
16 Nov – 12 Dec 2026
Berlin | Online
Early bird
6,300+
Graduates
4.9/5
Rating
98%
Success rate
"
The MLOps week was exactly what I needed. I'd been training models locally for years but had no idea how to get them into production. Now I know — and my team values me completely differently.
PL
Patrick L.
Data Scientist → Cloud ML Engineer, Berlin
Is this course right for you?

It's built for you if…

You work in IT, data or engineering and want to specialise in cloud AI
You have data science skills but struggle to deploy models to production
You want a recognised cloud AI qualification that the market is paying for
You'd like the Jobcenter or QCG to fund the training
Getting started is easy

How to join — 3 simple steps

1

Free consultation

Book a 30-minute call. We check if you qualify for funding — no obligation.

2

We handle the paperwork

We guide you through the Bildungsgutschein or QCG application, step by step.

3

Start learning — for free

Join the next cohort online or in Berlin. Zero cost to eligible participants.

After the course

By the end, you'll be able to…

Deploy and configure AI services on AWS and Azure from scratch
Build MLOps pipelines that take models from training to production automatically
Scale inference endpoints to handle real-world traffic loads
Process large datasets using cloud-native big data services
Implement IAM, encryption and compliance controls for AI workloads
Design cloud architectures that are cost-efficient and AI-ready

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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