Cloud-Based AI Solution Design Patterns
How do you build scalable AI data architectures in the cloud? What are the best techniques for optimizing distributed AI model training in cloud environments? How can you design resilient and cost-effective AI applications that utilize cloud-based autoscaling and serverless inference?
This new course delves into proven design patterns tailored for cloud-based AI, addressing challenges in data architecture, model training optimization, and resilient and scalable application deployment and operations.
Join me as we cover these techniques and how to use them to create highly effective AI solutions designed to leverage cloud-based services, resources and infrastructure.
Check out the new course here:
Here is the TOC:
Introduction
Introduction
What You Need to Know
Systems and Platforms in the Cloud
Understanding Design Patterns
Chapter 1 - Cloud-Based Data-Centric Design Patterns
Data-Centric Design Patterns Overview
Serverless Data Pipeline
Distributed Feature Store
Continuous Data Validation
Hybrid Data Processing
Recommended by LinkedIn
Chapter 2 - Cloud-Based Model-Centric Design Patterns
Model-Centric Design Patterns Overview
Distributed AI Model Training
AI Model Operations Monitoring and Optimization
AI Model Drift Detection
Federated AI Learning
Chapter 3 - Cloud-Based Application-Centric Design Patterns
Application-Centric Design Patterns Overview
AI Workload Autoscaling
Containerized AI Model Deployment
Serverless AI Inference
Chapter 4 - Conclusion
Video 1 - Next Steps
About the Contributor
Thomas Erl is a LinkedIn Top Voice, a best-selling IT author and the AI and Technology Education Specialist with Arcitura, for whom he has developed over 50 courses about AI and numerous other digital technologies. He has authored and co-authored 15 books for the "Pearson Education Digital Enterprise Book Series from Thomas Erl", acts as the Senior AI Consultant for Transformative Digital Solutions, and is a LinkedIn Learning Content Developer and Instructor.
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Books, Videos, Podcasts by Thomas: thomaserl.com