Intensive training sessions on AI, Data Engineering, Cloud Architecture, and Forward Deployment — taught by engineers who've built at scale.
By practitioners from AWS, NVIDIA, and top-tier tech companies
CtrlSkill
Every industry is being reshaped by data and AI. The gap between building AI in a notebook and shipping it in production is massive. That's where skilled engineers come in — and that's what CtrlSkill trains you for.
Build and maintain pipelines that move, transform, and store data at scale. Spark, Airflow, Kafka, and cloud-native tools.
Design, train, and deploy ML models and LLM-powered apps. Embeddings, RAG, production inference, and monitoring.
The bridge between AI research and real-world impact. Architect solutions and deploy AI products that actually work.
Design scalable cloud architectures on AWS, GCP, or Azure. Event-driven systems, FinOps, and infrastructure as code.
Each session is hands-on and led by industry practitioners. Register early — seats are limited.
More sessions coming soon...
New sessions on Data Engineering, Cloud, and AI will be announced here.
Every trainer has shipped production systems at scale. They teach what they've actually built — not textbook theory.

Builds and scales modern data platforms at Accor — self-service analytics, automation, and reliable cloud data platforms. Shares his work through technical articles, podcasts, and community content on analytics engineering and AI-powered data solutions.

PhD from France and CEO of 38 Labs, with 10+ years shipping AI products as a Forward Deployed Engineer. Also an O'Reilly instructor — teaches practitioners how to bridge research and real-world production deployment.

Doctorate from France and CEO of Namla. Several years across cloud, AI, and edge-computing — focused on LLM integration, multi-agent orchestration, distributed infrastructure on Kubernetes, and enterprise AI adoption patterns.

Masters from France with 7+ years as a Data Engineer specializing in AWS. Has delivered data projects for TotalEnergies, L'Oréal, and Stellantis. Also teaches Data Engineering & Data Governance at EFREI Paris.
Real feedback from engineers, analysts, and students who joined our first sessions.
The session cleared up in four hours what I’d been trying to piece together from blog posts for months. Loved that it was hands-on with real case studies — not just slides.
Finally understood the difference between RAG and fine-tuning — and when to use each. The instructor answered every question in the chat. Rare for a free session.
Signed up because a colleague forwarded the LinkedIn post. Stayed because the trainer clearly ships this stuff for a living. The recap on the e-learning platform is a nice touch.
I’m a student and most free trainings are just funnels to a paid course. This wasn’t. Pure technical content, and I could revisit the recording on the learning platform.
The WhatsApp group before the session helped me come in with the right context. Timezone options meant I could join from Dubai without pulling an all-nighter.
Been in data for six years and still learned something new about deployment patterns. Looking forward to the deeper Data Engineering session announced next.
Not a lecture. Not a sales pitch. Real hands-on sessions built by practitioners.
Taught by engineers from AWS, NVIDIA, and top companies who've shipped at scale.
Live case studies and practical exercises. You build, not just watch.
Multiple timezone slots per session. Paris, Mumbai, Dubai, or New York — we've got you.
Pure technical content. Register, show up, and learn from the best.