DevOps and AI: Fundamentals, Methods, and Practical Application

Course overview

Objective The training provides comprehensive knowledge and practical skills in the areas of DevOps and Artificial Intelligence (AI). It aims to empower participants to design, implement, and optimize modern IT infrastructures and processes, as well as to utilize advanced AI technologies for innovative problem-solving. Content DevOps Foundation Fast Track Introduction to DevOps, its values, principles, and cultural aspects. Agile methods, service management, and the role of stakeholders in collaboration. DevOps culture, roles, toolchains, and core practices. Continuous Integration, Delivery, and Deployment (CI/CD), as well as testing methods and quality assurance. Containerization, microservices, and open-source technologies. Lean thinking, lean production, and the tool landscape in the DevOps environment. Metrics, Key Performance Indicators (KPIs), and performance measurement. Change management, resilience, and strategies for automation challenges. Scrum, Kanban, and scaled agile frameworks. Innovative practices such as ChatOps and Dojo. Value stream mapping, constraint management, and continuous improvement processes. Knowledge sharing and learning methods in the DevOps context. DevSecOps, Site Reliability Engineering (SRE), and application programming interfaces (APIs). AI Master Fundamentals of Artificial Intelligence, classical machine learning, as well as neural networks and deep learning. Functionality and application of generative AI, as well as the selection of suitable AI solutions. Designing AI-first strategies and planning AI-supported process optimizations. Configuration of AI assistants and agent systems, as well as their implementation in existing processes. Cybersecurity in the context of AI systems. Strategic AI marketing as a practical example. Conducting a practical project for the development of an AI system. Ethical, legal, and responsibility-related aspects of AI development. Industry-specific peculiarities and further perspectives. Learning Objectives Understanding the core concepts and principles of DevOps to improve IT processes. Application of agile methods and service management in the DevOps context. Implementation of Continuous Integration, Delivery, and Deployment. Mastery of techniques for measuring and improving IT performance. Grasping the fundamentals and functionalities of Artificial Intelligence and Machine Learning. Ability to select and apply suitable AI technologies for specific problems. Development of strategies for implementing AI in business processes. Conducting practical projects for creating AI applications. Awareness of ethical and legal issues in the field of AI. Career Prospects The acquired knowledge and skills qualify participants for roles in IT-related fields. This includes positions in IT management, software development, project management, system administration, and data analysis. Graduates are equipped to support the implementation and optimization of DevOps practices as well as the strate…

Upcoming dates

• 2026-09-27T22:00:00.000Z · 2027-01-14T23:00:00.000Z · Mannheim · Combined Learning
• 2026-09-27T22:00:00.000Z · 2027-01-14T23:00:00.000Z · Bremen · Combined Learning
• 2026-09-27T22:00:00.000Z · 2027-01-14T23:00:00.000Z · Potsdam · Combined Learning
• 2026-09-27T22:00:00.000Z · 2027-01-14T23:00:00.000Z · Hannover · Combined Learning
• 2026-09-27T22:00:00.000Z · 2026-11-19T23:00:00.000Z · Potsdam · Combined Learning