EU AI Act and DevOps Foundation

Course overview

Course Objective The training program provides comprehensive knowledge and practical skills in the field of Artificial Intelligence (AI) and the associated regulatory frameworks, as well as agile development methods. It aims to empower participants to understand the complexity of the EU AI Act and translate it into practical strategies to leverage AI opportunities. Furthermore, the principles and practices of DevOps are taught to enhance efficiency and agility in IT teams and improve collaboration. Content The "EU AI Act Certificate" course covers an introduction to the EU AI Act, its core concepts, scope, as well as basic terms and definitions. The risk classification of AI systems, specific requirements for high-risk AI systems, conformity assessment and certification processes are explained in detail. Additionally, topics such as documentation, monitoring, sanctions, liability issues, and personal risks are addressed. Another focus is on monitoring, market supervision, and compliance management, as well as the practical implementation of obligations. Global perspectives and future outlooks of AI legislation round off this part. The "DevOps Foundation" course introduces the fundamentals and emergence of DevOps and highlights the cultural-philosophical approach. Key topics include the basic understanding of DevOps, stakeholder management and collaboration, as well as culture, organization, and change enablement. Reasons for using DevOps and common misunderstandings are addressed. Central DevOps practices such as Continuous Everything, value stream, deployment pipeline, version control, configuration management, and value stream thinking are taught. The Definition of Done (DoD), strategies for typical automation challenges, and DevOps anti-patterns are also part of the course. Service management as an enabler for DevOps, key practices, metrics and KPIs, the interplay of DevOps and Scrum, DevSecOps with security best practices, and the connection of DevOps with Lean/Kanban are covered. The measurement and improvement with DevOps, practical application, and knowledge sharing are the focus. Finally, AI in DevOps (GenAI, AIOps) and exam preparation are discussed. Learning Objectives Understanding of the regulatory requirements of the EU AI Act. Ability to classify AI systems according to risk levels. Knowledge of processes for conformity assessment and certification of AI systems. Competence in the practical implementation of compliance obligations in the AI field. Understanding of the cultural and technical principles of DevOps. Ability to implement central DevOps practices to increase efficiency and agility. Knowledge of methods to improve workflows and ensure quality in IT projects. Ability to apply metrics and KPIs to measure and improve DevOps initiatives. Understanding of the integration of security practices (DevSecOps) into DevOps workflows. Ability to utilize AI tools to support DevOps processes. Career Prospects The acquired knowledge and…

Upcoming dates

• 2026-10-25T23:00:00.000Z · 2026-12-17T23:00:00.000Z · Darmstadt · Combined Learning
• 2026-10-25T23:00:00.000Z · 2026-12-17T23:00:00.000Z · Berlin · Combined Learning
• 2026-10-25T23:00:00.000Z · 2027-02-11T23:00:00.000Z · Hamburg · Combined Learning
• 2026-10-25T23:00:00.000Z · 2026-12-17T23:00:00.000Z · Münster, Westfalen · Combined Learning
• 2026-10-25T23:00:00.000Z · 2027-02-11T23:00:00.000Z · Dortmund · Combined Learning