NVIDIA Free Online Courses on AI: A Comprehensive Guide

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2025-02-12

NVIDIA has recently released a series of free online courses focused on Artificial Intelligence (AI). These courses are designed to cater to a wide range of learners, from beginners to advanced practitioners. Below is a detailed overview of the courses, along with practical commands and codes to help you get started.

1. Generative AI Explained

Learning Objectives:

  • Define Generative AI and explain how it works.
  • Describe various Generative AI applications.
  • Explain the challenges and opportunities in Generative AI.

Practical Command:


<h1>Install necessary libraries for Generative AI</h1>

pip install tensorflow keras
  1. AI for All: From Basics to GenAI Practice

Learning Objectives:

  • Understand AI’s impact on industries like healthcare and autonomous vehicles.
  • Transition from machine learning to generative AI.
  • Create music, images, and videos using GenAI.

Practical Command:


<h1>Clone a repository for AI basics</h1>

git clone https://github.com/example/ai-basics.git
cd ai-basics

3. Getting Started with AI on Jetson Nano

Learning Objectives:

  • Set up your Jetson Nano and camera.
  • Collect and annotate image data for classification and regression models.
  • Train a neural network on your data.

Practical Command:


<h1>Set up Jetson Nano</h1>

sudo apt-get update
sudo apt-get install python3-pip
pip3 install jetson-inference

4. Building A Brain in 10 Minutes

Learning Objectives:

  • Understand how neural networks use data to learn.
  • Grasp the math behind a neuron.

Practical Command:


<h1>Simple neural network in Python</h1>

import numpy as np

<h1>Define a simple neuron</h1>

def neuron(inputs, weights, bias):
return np.dot(inputs, weights) + bias

5. Building Video AI Applications on Jetson Nano

Learning Objectives:

  • Create DeepStream pipelines for video processing.
  • Handle multiple video streams.
  • Use alternate inference engines like YOLO.

Practical Command:


<h1>Install DeepStream SDK</h1>

sudo apt-get install deepstream-5.0

6. Building RAG Agents with LLMs

Learning Objectives:

  • Explore scalable deployment strategies.
  • Learn about microservices and development.
  • Experiment with LangChain paradigms for dialog management.

Practical Command:


<h1>Install LangChain</h1>

pip install langchain
  1. Accelerate Data Science Workflows with Zero Code Changes

Learning Objectives:

  • Learn the benefits of unified CPU and GPU workflows.
  • GPU-accelerate data processing and machine learning.
  • See faster processing times with GPU.

Practical Command:


<h1>Install RAPIDS for GPU-accelerated data science</h1>

conda install -c rapidsai -c nvidia -c conda-forge rapids=21.06

9. to AI in the Data Center

Learning Objectives:

  • Basics of AI, machine learning, and GPU architecture.
  • Deep learning frameworks and AI workload deployment.
  • Learn about multi-system AI clusters and infrastructure planning.

Practical Command:


<h1>Install CUDA for GPU computing</h1>

sudo apt-get install nvidia-cuda-toolkit

What Undercode Say

The NVIDIA free online courses on AI provide an excellent opportunity for anyone interested in diving into the world of artificial intelligence. These courses cover a broad spectrum of topics, from the basics of AI to advanced applications like generative AI and video processing. By following the practical commands and codes provided, you can set up your environment and start experimenting with AI models right away.

For those interested in deep learning, the Jetson Nano setup commands will help you get started with hardware acceleration. The installation of libraries like TensorFlow, Keras, and RAPIDS will enable you to build and train neural networks efficiently. Additionally, the DeepStream SDK commands will assist you in creating video AI applications, while LangChain will help you manage dialog systems in RAG agents.

To further enhance your learning, consider exploring the following resources:
– NVIDIA Developer
– TensorFlow Official Documentation
– Keras Official Documentation
– RAPIDS AI

By leveraging these resources and the practical commands provided, you can significantly accelerate your journey into AI and machine learning. Whether you are a beginner or an experienced practitioner, these courses offer valuable insights and hands-on experience that will help you stay ahead in the rapidly evolving field of AI.

References:

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