Learn what AI is and how NVIDIA's GPU technologies and solutions take it to the next level.

Designed for enterprise IT professionals and Administrators this course explores an introduction to AI, GPU computing, NVIDIA AI software architecture, and how to implement and scale AI workloads in the data center.

What will I learn?

• AI use cases for healthcare, autonomous vehicles, and data center optimization.
• AI concepts such as machine learning, deep learning, inferencing, and training.
• The history of GPUs, GPU architecture, and the difference between GPUs and CPUs.
• NVIDIA AI software architecture, including frameworks and container repositories.
• Hardware and facilities planning, including servers, networking, storage, management, power, and cooling.

Course Objectives

Upon completion, you’ll understand how AI is transforming society and how to deploy GPU computing to the data center to facilitate this transformation.

Audience

• IT Professionals
• System and Network Administrators 
• DevOps 
• Datacenter professionals

Prerequisites

There are no prerequisites for this class

Course Topics

1. GPU Computing in the Data Center (20 min)
2. Introduction to Artificial Intelligence (20 min)
3. Introduction to GPUs (15 min)
4. GPU Software Ecosystem (20 min)
5. Server Level Considerations (25 min)
6. Rack Level Considerations (45 min)
7. Data Center Level Considerations (50 min)