In this module you will see AI use cases in different industries, the concepts of AI, Machine Learning (ML) and Deep Learning (DL), understand what a GPU is, the differences between a GPU and a CPU. You will learn about the software ecosystem that has allowed developers to make use of GPU computing for data science and considerations when deploying AI workloads on a data center on prem, in the cloud, on a hybrid model, or on a multi-cloud environment.
Learning Objectives
- Learn about different hardware offerings in NVIDIA GPU Portfolio
- Learn about NVIDIA Data Center Platfrom
- Understand how NVIDIA is extending AI to every enterprise using virtualization with NVIDIA AI enterprise
- Become Familiar with NVIDIA Software stack and CUDA-X AI software acceleration libraries
- Learn about NVIDIA GPU Architecture
- Understand Key differences between CPUs to GPUs
- Learn about Machine Learning (ML) and Deep Learning (DL)
- Learn about AI use cases such as: AI in Healthcare, Autonomous Vehicles, and AI in financial services
- Learn terminology and concepts related to AI
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