Artificial Intelligence Job Description
March 24, 2025
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Instructor: NVIDIA Training
45,826 already enrolled
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(333 reviews)
(333 reviews)
Explore diverse applications of AI across various industries. Understand concepts like Machine Learning, Deep Leaning, training and inference.
Trace the evolution of AI Technologies. From its inception to the revolutionary advances brought by Generative AI, and the role of GPUs.
You will become familiar with deep learning frameworks and AI software stack.
Learn about considerations when deploying AI workloads on a data center on prem, in the cloud, on a hybrid model, or on a multi-cloud environment.
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Artificial Intelligence, or AI, is transforming society in many ways.
From speech recognition to self-driving cars, to the immense possibilities offered by generative AI. AI technology provides enterprises with the compute power, tools, and algorithms their teams need to do their life’s work. Designed for enterprise professionals, this course provides invaluable insights into the ever-changing realm of AI. Whether you're a seasoned professional or just beginning your journey into AI, this course is essential for staying ahead in today's rapidly evolving technological landscape. We start the journey with an Introduction to AI where we cover AI basic concepts and principles. Then, we delve into data center and cloud infrastructure followed by AI operations. This course is part of the preparation material for the “NVIDIA-Certified Associate: AI Infrastructure and Operations" certification. Successfully completing this exam will allow you to showcase your expertise and support your professional development. Who should take this course? * IT Professionals * System and Network Administrators * DevOps Engineers * Datacenter professionals No prior experience required. Let's get started!
In this module, you will explore AI applications across various industries and delve into fundamental concepts of AI, Machine Learning (ML), and Deep Learning (DL). Additionally, the course will introduce you to Generative AI, how Large Language Models (LLMs) work and new business opportunities being unlocked with this new technology. You will understand what a GPU is, distinguish the key differences between GPUs and CPUs, and delve into the software ecosystem enabling developers to harness GPU computing for data science. Finally, you will learn considerations for deploying AI workloads across different infrastructures, from on-premises data centers to models and multi-cloud setups.
7 videos6 readings5 assignments
In this module, we will visit infrastructure level considerations when deploying AI clusters. You will learn about requirements for multi-system AI clusters, such as the capabilities of NVIDIA GPUs and CPUs to address the requirements of AI workloads, storage, and networking considerations. We will discuss how energy efficient computing practices help data centers lower their carbon footprint, and how recommended design documents, or Reference Architectures (RAs), can be used as a foundation for building best-of-breed optimized AI systems. We will end this module discussing how cloud computing enhances AI deployments, outlining the key considerations for deploying AI in the cloud.
14 videos6 readings13 assignments
This last module covers key aspects involved in infrastructure management, monitoring, cluster orchestration, and job scheduling. You will identify the general concepts about provisioning, managing, and monitoring AI infrastructure, and describe the value and tools for cluster management. Finally, you will learn the key differences and common tools used for orchestration and scheduling, and the value of MLOps tools for continuous delivery and automation of AI workloads.
2 videos2 readings2 assignments
It is highly recommended that you complete all the course activities before you begin the quiz. Good luck!
1 video1 reading1 assignment
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NVIDIA Training offers resources for diverse learning needs – from learning materials to self-paced and live training to educator programs – giving individuals, teams, organizations, educators, and students what they need to advance their knowledge in AI, accelerated computing, accelerated graphics and simulation, and more. Whether you’re interested in application development, infrastructure management, or general AI technologies, you’ll find targeted training resources at www.nvidia.com/en-us/learn/enterprise.
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Course
Scrimba
Specialization
DeepLearning.AI
Course
Infosec
Course
333 reviews
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Reviewed on Jan 26, 2025
Good overview courses on AI infrastructure. I understand the Nvidia AI infrastructure portfolio better now than before.
Reviewed on Nov 5, 2024
More detail about what actually NVIDIA is offering with specification need to be provided
Reviewed on Mar 24, 2025
A very Good Course for Core Infrastructure and Datacenter Management personnel who wants to know the fundamentals of AI Infrastructure.
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