intermediate 
1 Day Who is this course intended for?
This course is designed for IT decision-makers, infrastructure architects, cloud architects, and technology professionals seeking to understand AI infrastructure requirements and enterprise AI deployment strategies.
What is AI Infrastructure?
AI Infrastructure refers to the combination of compute, networking, storage, software, and orchestration components required to train, deploy, and manage AI models at scale.
What is Google Cloud AI Hypercomputer?
Google Cloud AI Hypercomputer is Google’s integrated AI infrastructure architecture designed to optimize performance, scalability, and efficiency for AI training and inference workloads.
What accelerators are covered in the course?
The course covers Graphics Processing Units (GPUs) and Tensor Processing Units (TPUs), including their architectures, use cases, and selection considerations.
Will I learn how to choose between GPUs and TPUs?
Yes. The course explains workload characteristics, performance considerations, and best practices for selecting the most cost-effective accelerator for specific AI workloads.
What is training goodput?
Training goodput refers to the effective training performance achieved after accounting for infrastructure bottlenecks, networking delays, and resource inefficiencies.
Does the course cover storage and networking?
Yes. Participants learn how networking and storage architectures impact AI training performance, data ingestion, and inference workloads.
Is this a hands-on technical implementation course?
No. The course focuses on infrastructure concepts, architecture decisions, resource optimization, and strategic planning rather than implementation-level configuration.
Will I receive a certificate?
Yes. A CloudThat Course Completion Certificate will be awarded upon successful completion.
How long is the training?
The course duration is 3 hours and is delivered as an instructor-led training program.
