Architect AI Systems: From Concept to Code
About this course
This course helps you design AI system architectures using SysML and MBSE. You’ll model how requirements connect to components, how data flows across the system, and how retraining cycles are triggered. Through videos, readings, hands-on modeling, and a coding lab, you will build requirement diagrams, block structures, and a programmatically generated sequence diagram using Python. By the end, you’ll be able to translate AI concepts into architecture artifacts that teams can code against—supporting reliability, provenance, and auditability.
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What you'll learn
- Create SysML requirement diagrams for AI projects
- Design block definition diagrams that capture component relationships
- Model data flow and retraining cycles within an AI system
- Generate sequence diagrams automatically with Python scripts
- Produce architecture artifacts that can be handed off to development teams
Course objectives
- Apply model‑based systems engineering principles to AI system design
- Translate AI concepts into concrete architecture models
- Integrate Python coding to automate diagram generation
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