Building real-world Azure, AWS and AI projects while documenting the journey in public. Based in Zurich 🇨🇭
Real-world labs and projects — not just theory.
Built a secure cloud environment with Linux and Windows VMs, Virtual Networks, Subnets, NSGs and SSH/RDP access.
View on GitHub →Deploying core AWS infrastructure with EC2, VPC, Security Groups and IAM — building hands-on experience with the AWS ecosystem.
Coming soon →Exploring Azure AI services, machine learning concepts and practical AI integrations — preparing for the AI-900 certification.
In progress →My active learning tracks right now.
Documenting the journey — labs, certs and insights.
How I set up VMs, VNets, NSGs and secure access in Azure — step by step.
My study strategy, resources used, and lessons learned from the Azure Fundamentals exam.
The reason I decided to combine cloud engineering with AI — and what my roadmap looks like.
Hands-on labs and builds across Azure, AWS and AI.
Built a secure Azure environment with Linux + Windows VMs, Virtual Network, Subnet, Network Security Groups, SSH/RDP access controls and Public IPs.
View on GitHub →Configuring Azure Blob Storage, Access Tiers, Lifecycle Management and SAS tokens for secure data access — coming soon.
🔧 In ProgressBuilding core AWS networking with VPC, public/private subnets, EC2 instances and Security Groups — mirroring the Azure lab on AWS.
🔧 In ProgressConfiguring IAM users, groups, roles and least-privilege policies — understanding identity and access management in AWS.
📋 PlannedExploring Azure Cognitive Services, Computer Vision, Language Understanding and Azure ML — hands-on preparation for AI-900.
🔧 In ProgressBuilding Python scripts for Azure SDK, cloud automation and basic ML models — learning by doing with real cloud integrations.
📋 PlannedCredentials that validate real hands-on knowledge.
Core Azure cloud concepts including compute, networking, storage, identity, security, governance, and pricing. Demonstrates solid understanding of what Azure offers and how to navigate the ecosystem.
AI workloads and considerations, machine learning principles, Computer Vision, Natural Language Processing, and conversational AI on Azure. Actively building labs to complement the theory.
Labs, certifications and insights — documented as I go.
A step-by-step walkthrough of how I built a secure Azure environment with VMs, Virtual Networks, NSGs and access controls — including the architecture diagram.
My study plan, resources, and honest take on what matters and what doesn't when preparing for the Azure Fundamentals exam.
Cloud infrastructure is the foundation — but AI is where the industry is heading. Here's why I'm combining both and what my roadmap looks like.
I'm an IT professional based in Zurich, Switzerland, transitioning into cloud and AI engineering. After years in IT, I decided to go all-in on the technologies shaping the future.
My focus is on building real-world infrastructure — not just following tutorials, but designing, deploying and documenting complete cloud environments from scratch.
I believe the best way to learn is to build in public. Every lab, every failure, every fix gets documented — on this site and on GitHub.
Open to opportunities, collaborations and cloud conversations. Based in Zurich 🇨🇭