NVIDIA, a pivotal force in the AI revolution, has significantly simplified the process of learning Artificial Intelligence through its newest course offerings. Below, you’ll find five free courses that offer exceptional value—rest assured, their benefits are as substantial as gold. These selections are particularly suited for beginners and represent some of the best starting points to enhance your knowledge and skills in AI.

Generative AI Explained

Generative AI describes technologies that are used to generate new content based on a variety of inputs. In recent time, Generative AI involves the use of neural networks to identify patterns and structures within existing data to generate new content. In this course, you will learn Generative AI concepts, applications, as well as the challenges and opportunities in this exciting field.

Learning Objective

• Define Generative AI and explain how Generative AI works
• Describe various Generative AI application
• Explain the challenges and opportunities in Generative AI

Explore this Free Generative AI course by NVIDIA here.

Building a Brain in 10 Minutes

This course notebook dives into the fascinating world of neural networks, exploring the biological and psychological inspirations behind these groundbreaking models. While the code can be run by anyone, a basic understanding of Python 3 programming concepts (functions, loops, dictionaries, and arrays) will help you grasp the inner workings effectively. Additionally, familiarity with calculating regression lines will prove beneficial. To expand your knowledge further, check out the follow-up course “Getting Started with Deep Learning” or explore other online offerings from NVIDIA DLI.

Learning Objectives

• Exploring how neural networks use data to learn
• Understanding the math behind a neuron

Explore this Free Generative AI course here.

Augment your LLM with Retrieval Augmented Generation

Retrieval Augmented Generation (RAG) – Introduced by Facebook AI Research in 2020, is an architecture used to optimize the output of an LLM with dynamic, domain specific data without the need of retraining the model. RAG is an end-to-end architecture that combines an information retrieval component with a response generator. In this introduction we provide a starting point using components we at NVIDIA have used internally. This workflow will jumpstart you on your LLM and RAG journey.

Learning Objectives

• Understand the basics of Retrieval Augmented Generation.
• Learn about the RAG retreival process
• Learn about NVIDIA AI Foundations and the components that constitue a RAG model.

Explore this Free Generative AI Course by NVIDIA here.

Also Read: Top 7 Generative AI Courses to Do in 2024

Building RAG Agents with LLMs

Agents powered by large language models (LLMs) are quickly gaining popularity from both individuals and companies as people are finding new emerging capabilities and opportunities to greatly improve their productivity. An especially powerful recent development has been the popularization of retrieval-based LLM systems that can hold informed conversations by using tools, looking at documents, and planning their approaches. These systems are very fun to experiment with and offer unprecedented opportunities to make life easier, but also require many queries to large deep learning models and need to be implemented efficiently. This course will observe how you can deploy an agent system in practice and scale up your system to meet the demands of users and customers.

Learning Objective

• Explore scalable deployment strategies for LLMs and vector databases.
• Learn about microservices, how to work between them, and how to develop your own.
• Experiment with modern LangChain paradigms to develop dialog management and document retrieval solutions.
• Get practice with state-of-the-art models with clear next steps regarding productionalization and framework exploration.

Checkout this Free Generative AI Course by NVIDIA here.

Accelerate Data Science Workflows with Zero Code Changes

Across industries, modern data science requires large amounts of data to be processed quickly and efficiently. These workloads need to be accelerated to ensure prompt results and increase overall productivity. NVIDIA RAPIDS offers a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes. In this workshop, you’ll learn to use RAPIDS to speed up your CPU-based data science workflows.

Learning Objectives

By participating in this course, you will:

• Understand the benefits of a unified workflow across CPUs and GPUs for data science tasks
• Learn how to GPU-accelerate various data processing and machine learning workflows with zero code changes
• Experience the significant reduction in processing time when workflows are GPU-accelerated

You can explore Free Generative AI Course by NVIDIA here.

Other Free Courses by NVIDIA

For those eager to explore further, NVIDIA’s website boasts a total of 16 free courses. Explore the recommended courses by clicking on the following link: NVIDIA’s Free Courses.

Conclusion

NVIDIA’s free AI courses are revolutionizing AI education! They offer a wealth of knowledge with 16 courses on fascinating topics like Generative AI and neural networks. In fact, I’ve checked these courses myself and found them incredibly informative.

That’s why I urge you to join me on this journey!

But if you’re ready to take your skills to the next level, dive into the future of AI with the GenAI Pinnacle Program. Master cutting-edge Generative AI alongside industry experts, build real-world projects & unlock your potential.