Take your software architecture skills to the next level and learn how to develop robust, customizable architectures for ML and AI systems.
In our practice-oriented training course “Software Architecture for AI and ML Systems (SWARC4AI)”, you will learn how to successfully integrate ML components into modern software architectures. You will learn what is important when designing long-lasting, scalable and secure architectures for AI-supported systems - from data acquisition and processing to the use of LLMs, operation and further development.
The training is aimed at software architects and developers who have already gained initial experience with machine learning and now want to learn how to embed ML systems sustainably in software architectures.
Our SWARC4AI training is not a frontal event - you will work intensively on practical case studies. In small teams, you will formulate ML problems, prepare data, develop features, select models and train or adapt them. You will exchange ideas with other participants, discuss possible solutions and benefit from different perspectives. Our trainers support you with impulses, questions and assistance - for independent and sustainable learning.
Agenda
- Integration of machine learning systems into existing software architectures
- Designing architectures for data acquisition, processing, persistence and utilization
- Dealing with architectural requirements such as scalability, maintainability and ethical responsibility
- Overview of different ML and LLM models and their impact on architecture
- Recognizing and dealing with problems such as model drift or data bias
- Integration of LLMs into architecture concepts
- Legal, ethical and security-related aspects when using AI systems
Your Benefits
High practical orientation through case studies and hands-on phases
Intensive exchange of experience with other participants
Supervision by experienced trainers from software architecture and ML practice
Official iSAQB certificate with 20 technology and 10 methodology credit points
Audience
This training is just right for you if you:
- have some experience with machine learning (e.g. simple model training in Python),
- have a basic understanding of software architecture, DevOps and APIs,
- are confident in Python and typical libraries such as scikit-learn, pandas or PyTorch,
- want to develop architectures that sustainably support ML systems.
Your Trainers
Alexander Kaserbacher
embarc
AI Engineering, Agentic Software Engineering
- Agile Software Architecture
- Architecting for Agentic Engineering
- CPSA Foundation Level
- Designing software architectures for AI and ML systems
- Domain-driven Design in Practice
- Flexible architectures
- Team Topologies Deep Dive
Alexander Kaserbacher is a consultant and trainer for software architecture at embarc. Several years of experience in agile software development help him to convey the added value of software architecture and to implement it effectively. In addition to cloud applications, distributed systems and evolutionary architecture, his passion for technology also includes the various impacts of software on companies and societal factors.
Dr. Felix Kammerlander
embarc
Agile software development, requirements engineering, software architecture
- CPSA Foundation Level
- Designing software architectures for AI and ML systems
- Domain-driven Design in Practice
As a consultant and trainer for software architecture, Felix is passionate about complex challenges. It is not only the technical solution that is important to him, but above all the attitude of a team. Thematically, he deals with application architecture and cross-team processes - his experience in requirements management and agile development projects flows directly into this. He is in his element when it comes to designing efficient architectures and ensures clear requirements, optimizes interfaces and orchestrates implementation across different teams.
Lara Pourabdolrahim
INNOQ GmbH
Machine Learning, AI
- Designing software architectures for AI and ML systems
Lara Pourabdolrahim works as a consultant at INNOQ. In addition to backend and frontend web development, her focus is on AI and machine learning in particular.