Software Architecture for AI Systems. Practical, compact, and actionable.

The training combines theoretical knowledge with practical exercises and real-world case studies. It provides fundamental knowledge in AI development, machine learning (ML), and generative AI (GenAI) as a basis for architectural design. Participants learn how to develop data-driven architectures that meet the highest standards of compliance and quality.

Upon completion of the training, they will be well-prepared to successfully implement AI projects—from the initial idea to integration into production systems.

This course is designed for anyone looking to efficiently integrate AI solutions into existing IT landscapes while focusing on scalability, security, and maintainability.

What to Expect?

In the SWARC4AI training, you will gain practical knowledge and tools to develop scalable software architectures for AI. You will learn how to combine machine learning, generative AI, and traditional approaches to create hybrid, future-proof systems. The focus is on integrating AI into existing IT landscapes while ensuring scalability, security, and maintainability.

Prerequisites for Participants

➤ A basic understanding of artificial intelligence, machine learning, and data science
➤ A fundamental understanding of software architecture and the design of software systems, APIs, and DevOps
➤ Basic knowledge of the Python programming language and its use for AI problems
➤ Overview of common libraries such as scikit-learn, tensorflow, PyTorch, etc.
➤ Experience with the Linux command line is helpful

Technical Requirements

There are no specific requirements for the training environment, as the exercises are conducted using cloud-based and web-based tools such as Miro, Draw.io, and platforms like Jupyter or HuggingFace. A stable and sufficiently fast internet connection is the only requirement.

Your Added Value

➤ You will gain knowledge in modern software architecture for AI systems.
➤ You will learn how to combine machine learning, generative AI, and traditional software approaches into hybrid systems.
➤ You will acquire practical knowledge on integrating AI into existing IT landscapes.
➤ You will learn how to develop scalable, maintainable, and extendable AI solutions.
➤ You will gain knowledge in adhering to security, compliance, and data protection requirements.
➤ You will learn how to address ethical issues related to AI.

Training Content in Detail

✔️ Introduction to AI Software Architecture
➤ Fundamentals of artificial intelligence, machine learning, deep learning, and generative AI.
➤ Typical use cases and potential risks of AI systems.

✔️ Compliance, Security, and Ethical Challenges
➤ Data protection laws (e.g., EU AI Act) and security requirements.
➤ Ethical and societal aspects in AI development.

✔️ Design and Development of AI Systems
➤ Lifecycle of ML projects and best practices.
➤ Design patterns for maintainable and scalable AI solutions.

✔️ Efficient Data Management
➤ Data acquisition, labeling, and processing.
➤ Building robust data pipelines and storage solutions.

✔️ Quality Characteristics and Operation of AI Systems
➤ Hardware requirements, monitoring, and sustainable AI usage.

✔️ System Architectures and Platforms for Generative AI
➤ Integrating AI into existing IT landscapes.
➤ Future-proof design patterns and evaluation frameworks.

✔️ Case Studies and Practical Projects
➤ Applying the learned content to real-world scenarios and concrete challenges.

The four-day training is designed for the practical application and deepening of the training content. Using a case study, participants will gain initial experience in software architecture design for AI systems, thereby laying a high-quality foundation for their own AI-based applications and systems. The entire software development cycle for AI-based systems will be covered.

Your Benefits at a Glance