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NVIDIA's List of Free Artificial Intelligence Courses

Haebom
Free NVIDIA lectures presented by His Majesty Jensen HuangIntroduction to AI in the Data CenterGenerative AI ExplainedBuilding a Brain in 10 MinutesBuilding RAG Agents with LLMsAugment your LLM Using Retrieval Augmented GenerationGetting Started with AI on Jetson NanoBuilding Video AI Applications at the Edge on Jetson NanoAccelerate Data Science Workflows with Zero Code Changes
NVIDIA originally started as a company making GPUs for gaming, but has evolved into a leader in AI technology. This shift began when they discovered tensor cores during their research to advance their graphics cards. These tensor cores are now used to train large language models (LLMs).
NVIDIA's technology brought innovation not just to hardware, but also to software. In particular, CUDA serves as a software platform for GPU parallel computing, making it easy for developers to leverage GPU power. CUDA has become a standard for GPU-accelerated computing and is widely used in areas like scientific computing, AI, and machine learning. Well, this has led to a skyrocketing NVIDIA stock price and soaring chip demand...
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Free NVIDIA lectures presented by His Majesty Jensen Huang

Based on these technological achievements, NVIDIA has begun offering several free self-paced courses to educate the general public about AI technology. These courses, available through the Deep Learning Institute, include the following:
Personally, I recommend taking the courses in the order below. They're great for getting a basic understanding of Jetson Nano, RAPIDS, and CUDA. As preview lectures, they're quite satisfying, though a bit lacking as practical training for actual work. These are good for grasping terminology or the overall flow. I think trying out things as toy projects, like with Jetson Nano, would be helpful.
NVIDIA also offers paid lectures and certifications, so if you're interested, feel free to check them out. As always, the best way to learn is by creating something yourself. Cheering you on!
NVIDIA Academy Courses Catalog.pdf712.02KB
젠슨황옹,,, 가죽자켓이 더욱 빛나 보이십니다.

Introduction to AI in the Data Center

Through this Coursera course, you'll learn how to deploy AI workloads in your data center. From speech recognition to improvements in supply chain management, AI technologies deliver the computing power, tools, and algorithms that companies need for daily operations. So how does AI work in a data center? What hardware and software infrastructure is required? This course introduces the key concepts and terminology to get you started on your data center's journey to AI and GPU computing.

Generative AI Explained

This lecture explains how generative AI creates new content from various inputs. Recently, this has included methods that use neural networks to recognize patterns and structures in existing data and generate new content.

Building a Brain in 10 Minutes

This lecture delves into the biological and psychological backgrounds that inspired the world's first neural networks. The learning goals are to explore how neural networks learn from data and to understand the mathematical principles behind neurons. Through this course, participants will gain a deep understanding of how neural networks learn and the math underlying neurons. To get the most from this course, it's recommended you have a grasp of basic programming concepts in Python 3 (like functions, loops, dictionaries, arrays, etc.) and knowledge of how to compute regression lines.

Building RAG Agents with LLMs

This course shows how to make language models more than just automation tools, turning them into productivity partners that can interact with various tools and documents to have informed conversations. You’ll learn about using embedding models, enhancing search, setting up conversational safety controls, and how to build and modularize Retrieval-Augmented Generation (RAG) agents. These agents can explore research papers and deliver answers without fine-tuning.

Augment your LLM Using Retrieval Augmented Generation

This course introduces how to speed up your data workflows, aiming to help you learn workflows that save time when making decisions about vector databases, embedding models, and large language models (LLMs).

Getting Started with AI on Jetson Nano

The Jetson Nano can run multiple neural networks in parallel for applications such as image classification, object detection, segmentation, and speech processing. In this lecture, you'll learn how to build a deep learning classification project using computer vision models and Jupyter iPython notebooks on your Jetson Nano.

Building Video AI Applications at the Edge on Jetson Nano

This course introduces how to build AI-based video understanding with the NVIDIA Jetson Nano Developer Kit. You'll get hands-on experience with platforms for intelligent video analytics (IVA) applications for the first time using the NVIDIA DeepStream SDK.

Accelerate Data Science Workflows with Zero Code Changes

In this course, you'll learn how to speed up CPU-based data science workflows using RAPIDS. NVIDIA RAPIDS provides a smooth experience for GPU-accelerating many existing data science tasks without any code changes. Participants will learn how to utilize RAPIDS to accelerate their CPU-based data science workflows.
NVIDIA’s educational offerings boost understanding and accessibility of AI tech, providing more technically literate people with a chance to step into programming. Even if the claim that “anyone can be a programmer” is a bit of an exaggeration, it’s a key step in making tech education more accessible.
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