AI Model Deployment
About
Deploying AI models efficiently is a critical challenge in modern AI solutions architecture. This module explores the key considerations in AI/ML deployment, including cloud provider offerings, cost-performance trade-offs, and strategies for scalable deployment. By the end of this session, you will be able to:
- Compare the AI/ML deployment options offered by major cloud vendors (AWS, Azure, GCP).
- Evaluate cost and performance trade-offs in different AI deployment strategies.
- Apply best practices to design scalable, reliable, and cost-efficient AI deployments.
This module prioritizes hands-on decision-making and problem-solving to prepare you for real-world AI deployment challenges.
Content Overview
| Lesson | Est. Delivery Time | Focus |
|---|---|---|
| Setup | 2 min | Set up the development environment |
| Hyperscaler Vendor Offerings | 30 min | Interactive decision-making on AWS, Azure, and GCP AI/ML services |
| Scalable AI Deployment Strategies | 35 min | Discover ways to balance cost and performance in AI deployments |
| Hands-on Exercise & Best Practices | 20 min | Apply deployment strategies and consolidate key takeaways |
Total Estimated Time: ~90 min