Detailed Course Outline
Module 1 - Foundations of AI Infrastructure
Topics:
- Definition of AI infrastructure
- The evolution of computing demands
- The need for new computing power
Objectives:
- N/A
Activities:
- N/A
Module 2 - Google Cloud’s AI Hypercomputer
Topics:
- The AI Hypercomputer
- The 3 layers of the AI Hypercomputer: Overview
Objectives:
- Differentiate between the layers of the AI Hypercomputer.
Activities:
- N/A
Module 3 - Compute Accelerators: GPUs and TPUs
Topics:
- Graphics Processing Units
- GPU architecture
- Google Cloud GPU family
- Selecting GPUs
- Tensor Processing Units
- TPU architecture
- Google Cloud TPU family
- Best practices and considerations
Objectives:
- item
Activities:
- 1x exercise/discussion
Module 4 - The AI Data Pipeline: Network and Storage
Topics:
- Maximizing goodput
- Networking for data ingestion and training
- Storage for data preparation and training
- Architecture for inference
Objectives:
- Evaluate storage and networking solutions to maximize training goodput.
Activities:
- 1x discussion
Module 5 - Orchestration and Consumption
Topics:
- Deployment options
- Flexible consumption
Objectives:
- Compare various deployment and consumption models for resource optimization.
Activities:
- N/A
Module 6 - Course Summary and Quiz
Topics:
- Course summary
- Q&A
- Quiz
Objectives:
- Differentiate between the layers of the AI Hypercomputer
- Select appropriate accelerators for the most cost effective AI workloads
- Evaluate storage and networking solutions to maximize training goodput
- Compare various deployment and consumption models for resource optimization
Activities:
- 1x quiz with 4 MCQs