GenAI and Predictive AI Architecture Foundations

Course details

Get a clear understanding of how AI solutions actually work, starting with their basic architectures and advancing to system components and architectural differences between generative AI and predictive AI systems. Join LinkedIn Top Voice and best-selling author Thomas Erl as he breaks down and explains, in plain English, the foundational building blocks and the primary moving parts behind contemporary AI solution environments. This course provides genuine insight into how AI systems function in the real world, and is essential for professionals already working with application and enterprise architectures, as well as professionals in the AI and data science fields.

Concepts

0. Introduction

01 - A behind-the-scenes look at AI systems
02 - What you need to know
03 - Essential terms and concepts

1. AI Solution Architecture Fundamentals

04 - Basic AI solution operational modes
05 - Basic AI architectural types
06 - Common AI solution components

2. Core AI System Architecture

07 - The data ingestion module
08 - The data preprocessing module
09 - The feature engineering module
10 - The inference engine module
11 - Data storage and model repository modules

3. AI Solution Monitoring Architecture

12 - Monitoring architecture overview
13 - Operational monitoring
14 - Data monitoring
15 - Model monitoring
16 - Ancillary monitors

4. Predictive AI Solution Architecture Considerations

17 - Core modules in predictive AI solutions
18 - Monitors in predictive AI solutions

5. Generative Solution Architecture Considerations

19 - Core modules in generative AI solutions
20 - Monitors in generative AI solutions

Conclusion

21 - Learn more about GenAI and predictive AI architecture