Welcome to the Introduction to AI in the Data Center Course! As you know, Artificial Intelligence, or AI, is transforming society in many ways. From speech recognition to improved supply chain management, AI technology provides enterprises with the compute power, tools, and algorithms their teams need to do their life’s work. But how does AI work in a Data Center? What hardware and software infrastructure are needed? These are some of the questions that this course will help you address. This course will cover an introduction to concepts and terminology that will help you start the journey to AI and GPU computing in the data center. You will learn about: * AI and AI use cases, Machine Learning, Deep Learning, and how training and inference happen in a Deep Learning Workflow. * The history and architecture of GPUs, how they differ from CPUs, and how they are revolutionizing AI. * Deep learning frameworks, AI software stack, 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. * Requirements for multi-system AI clusters, considerations for infrastructure planning, including servers, networking, and storage and tools for cluster management, monitoring and orchestration. This course is part of the preparation material for the NVIDIA Certified Associate - ”AI in the Data Center” certification. This certification will take your expertise to the next level and support your professional development. Who should take this course? * IT Professionals * System and Network Administrators * DevOps * Data Center Professionals No prior experience required. This is an introduction course to AI and GPU computing in the data center. To learn more about NVIDIA’s certification program, visit: https://academy.nvidia.com/en/nvidia-certified-associate-data-center/ So let's get started!