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AWS Training News

Together with the training team at tecRacer, we support companies in using AWS training effectively and purposefully.

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Dr. Melanie Peschmann
Unit Lead Training & Enablement

Public AWS Trainings – Upcoming Dates

Here’s the translation: Our current training courses combine technical expertise with hands-on project experience from real-world AWS environments. In May, the focus is clearly on production-ready AI and platform topics. Particularly relevant are trainings that help teams turn initial AI experiments into robust, scalable solutions.

Additional Open AWS Trainings:

AWS Technical Essentials

Date: May 25
Language: German

Secure your seat now!

Architecting on AWS

Date: May 26 – 28
Language: German

Secure your seat now!

AWS Cloud Practitioner Essentials

Date: June 8
Language: German

Secure your seat now!
All Open Trainings at a Glance

Enablement Focus of the Month

From Proof of Concept to Measurable Value: What AI Initiatives Need Now

Many organizations have already completed their first AI pilot projects. The technical possibilities are visible, enthusiasm is high, and initial proofs of concept often deliver compelling results. The harder part, however, comes next: the transition to stable, secure, and economically viable production solutions.

This is precisely where it becomes clear that successful AI adoption requires far more than model access or individual tools. What matters is having clear target outcomes, reliable data and integration pathways, governance, security requirements, and the ability to connect technical feasibility with real business value. Without this structure, many initiatives stall somewhere between prototype, production readiness, and actual value creation.

For organizations, this means AI must not only be experimented with, but systematically developed along the dimensions of business impact, technical feasibility, and organizational embedding. Only when these layers work together does an experiment become a robust solution with measurable value.

Enablement creates the foundation for this. It gives teams a shared language, helps prioritize realistic use cases, and supports making production-oriented decisions earlier and with greater confidence. This shortens the path from idea to implementation — and turns AI into a manageable, integral part of everyday business practice.

Training & Enablement

Why Role-Based Qualification Bridges the Gap Between Idea and Production

The closer AI initiatives get to production, the clearer it becomes: a single training for everyone is not enough. Business stakeholders need to be able to assess value, risks, and priorities. Architects and developers need a solid understanding of services, patterns, and integration considerations. Operations, security, and governance teams need to know how observability, control, and compliance work in practice.

Qualification is therefore most effective when it is built around roles. A shared foundational understanding provides orientation. Building on that, specialized training deepens exactly the skills that matter most for execution within each role. The result is not an isolated fragment of knowledge, but a coherent learning path aligned with real project requirements.

This approach is particularly powerful in the AWS context. New training courses on Agentic AI and production-ready Bedrock architectures, complementary platform and architecture trainings, and up-to-date certification paths help teams not only build knowledge, but translate it directly into concrete initiatives.

Training delivers knowledge. Enablement ensures that this knowledge flows into decisions, architecture work, and operational execution. Only in combination do they create the conditions needed to scale AI initiatives and develop them into economically viable, long-term solutions.

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