Lilly Tech Systems
Event-Driven AI Architecture
Build event-driven AI systems with Kafka, event sourcing, stream processing, and real-time inference.
Course Lessons
Follow these lessons in order for a complete understanding of event-driven ai architecture.
1. Event-Driven AI Overview
Learn about event-driven ai overview in the context of event-driven ai architecture.
2. Kafka for ML Pipelines
Learn about kafka for ml pipelines in the context of event-driven ai architecture.
3. Event Sourcing for AI
Learn about event sourcing for ai in the context of event-driven ai architecture.
4. Real-Time Feature Computing
Learn about real-time feature computing in the context of event-driven ai architecture.
5. Stream Processing Architecture
Learn about stream processing architecture in the context of event-driven ai architecture.
6. Event-Driven Inference
Learn about event-driven inference in the context of event-driven ai architecture.
7. Architecting for Events
Learn about architecting for events in the context of event-driven ai architecture.
What You'll Learn
By the end of this course, you will be able to:
Understand Core Concepts
Gain deep understanding of the principles and patterns that define event-driven ai architecture.
Apply in Practice
Implement real-world solutions using the architectural patterns and code examples from each lesson.
Make Architecture Decisions
Evaluate trade-offs and choose the right approaches for your specific requirements and constraints.
Build Production Systems
Design and implement production-ready AI systems that are reliable, scalable, and maintainable.