iSAQB® Software Architecture for AI Systems (SWARC4AI)
Design, development, and implementation (CPSA Advanced Level)
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Machine Learning Engineer
In this training course, you will acquire practical knowledge and tools for developing scalable software architectures for AI. You will learn how machine learning, generative AI, and classic approaches can be combined to create hybrid, future-proof systems. The focus is on integrating AI into existing IT landscapes, taking into account scalability, security, and maintainability.
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 social aspects in the development of AI.
Design and development of AI systems:
- Life cycle of ML projects and proven process models.
- 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:
- Requirements for hardware, monitoring, and sustainable AI use.
System architectures and platforms for generative AI:
- Integration of AI into existing IT landscapes.
- Future-proof design patterns and evaluation frameworks.
Case studies and practical projects:
- Applying what has been learned to real-life scenarios and specific challenges.
Requirements:
- A fundamental understanding of software architecture and the design of software systems, APIs, and DevOps.
- Basic knowledge of AI processes (machine learning, model training, MLOps, deployment, data pipelines).
Technical requirements:
There are no special requirements for the training environment, as the exercises take place using cloud- and web-based tools such as Miro, Draw.io, and platforms such as Jupyter or HuggingFace. All that is needed is a stable and sufficiently fast internet connection.
- You will acquire knowledge of modern software architecture for AI systems.
- You will learn how machine learning, generative AI, and classic software approaches are combined to form hybrid systems.
- You will acquire practical knowledge on integrating AI into existing IT landscapes.
- You will learn how to develop scalable, maintainable, and expandable AI solutions.
- You will acquire knowledge in the area of security, compliance, and data protection requirements.
- You will learn how to address ethical issues related to AI.
Your advantages at a glance:
- Practical content: The focus is on real-life examples and practical exercises.
- State-of-the-art concepts: Comprehensive knowledge of current trends and technologies is imparted.
- Efficient integration: Development of hybrid systems that optimally combine machine learning and classic software methods.
- Visual collaboration through, for example, whiteboarding
- High level of interactivity through customized exercises and breakout rooms
- Ideal trainer support even in the breakout rooms
Credit points for CPSA-A certification:
With the SWARC4AI training course, attendees earn attendees technical and 10 methodological credit points according to the iSAQB Advanced Level Program.
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