Modul SWARC4AI | 14. – 16. September 2026 | Berlin

Overview

The Modul SWARC4AI is an iSAQB Advanced Level training focused on software architecture for AI systems. The course explores how to design modern software architectures that effectively integrate AI components, including machine learning and generative AI. Participants learn to structure systems for scalability, security, explainability, and governance, with an emphasis on practical outcomes and real-world application. The module balances theory with hands-on exercises to help attendees translate concepts into tangible architectures for AI-enabled software.

Who should attend

This module is intended for software architects, technical leads, and senior developers who want to deepen their understanding of AI driven architectures. A foundational knowledge of machine learning, data processing, and software architecture is recommended to maximize the learning experience.

Format and delivery

The module combines lectures, hands-on sessions, and facilitated workshops. It is designed to support participants in integrating AI components into existing systems or in creating hybrids that leverage both traditional software patterns and AI capabilities. The program provides guidance on data governance, MLOps, model integration, and operational considerations for AI-enabled environments.

Agenda and sessions

• Introduction to AI related architecture concepts: machine learning basics, generative AI, and differences between AI systems and conventional software.
• Compliance, security, and alignment: EU AI Act considerations, privacy requirements, threat models, and risk mitigation.
• Design patterns for AI systems: architectural patterns for integrating ML, data pipelines, and AI components into larger software landscapes.
• Data management and processing: building robust data pipelines, data governance, and data quality across AI workflows.
• Quality attributes for AI operations: scalability, monitoring, observability, and MLOps practices for reliable AI software.
• Generative AI and AI tooling: patterns for LLM integration, retrieval augmented generation, and supporting tools.
• Case studies and practical projects: applying learned concepts to real world projects and case studies to reinforce understanding.

Speakers and format details

Expert trainers with industry experience guide the learning journey. The program emphasizes practical application, enabling attendees to relate course content to their own projects and environments.

Outcome

Participants gain a structured understanding of how to architect AI systems that are scalable, secure, and maintainable. They receive guidance on designing data flows, selecting appropriate AI patterns, and aligning AI initiatives with organizational governance and compliance requirements.

FAQ

• What prior knowledge is needed? Foundational knowledge of machine learning, data processing, and software architecture is recommended.
• Will there be hands-on exercises? Yes, the module includes workshops and practical sessions.
• Is the event online or in person? The page indicates Berlin as the location with an online attendance option noting online delivery. Attendees should verify the final delivery mode with the organizer.

Takeaway

A comprehensive, hands-on module that equips attendees to design and implement robust AI software architectures that balance innovation with governance and operational reliability.