NVIDIA has announced the release of five free online courses for those keen on deepening their understanding of AI. This initiative is particularly timely for individuals looking to make the most of their free time by expanding their knowledge in AI.
The importance of AI is becoming increasingly recognized across the tech industry, with major technology firms urgently seeking experts in this innovative field. Giants such as Microsoft, Google, and more recently Amazon, have already set a precedent by offering free online courses on AI. Following in these footsteps, NVIDIA, a significant player in the AI domain, has unveiled its own series of free courses. These courses cover a range of topics including AI, Deep Learning, Large Language Models (LLMs), and more.
NVIDIA’s new educational offerings are accessible through its website and other educational platforms like Coursera. However, potential learners should note that some of the courses may require a basic understanding of the subjects due to their advanced nature.
Free AI Courses by NVIDIA:
1. Generative AI Explained
Duration: 2 Hours
This course demystifies Generative AI’s workings, showcases its applications, and navigates through its challenges and opportunities, all while requiring a foundational grasp of Machine Learning and Deep Learning.
2. Building A Brain in 10 Minutes
Duration: 10 Minutes
This course delves into the biological and psychological roots of neural networks, offering an interactive experience to understand how these systems learn from data and the mathematical principles of neurons, designed for learners with a grasp of Python programming and basic regression analysis.
3. Augment your LLM Using Retrieval Augmented Generation
Duration: 1 Hour
This course introduces the Retrieval Augmented Generation (RAG) architecture, pioneered by Facebook AI Research, demonstrating how NVIDIA’s internal components can enhance an LLM with up-to-date, domain-specific data through an integrated retrieval and response generation system, and aims to equip learners with an understanding of RAG basics, its retrieval process, and the NVIDIA AI Foundations pivotal to a RAG model.
4. Building RAG Agents with LLMs
Duration: 8 Hours
Discover how to leverage the power of large language models (LLMs) to create RAG agents that enhance productivity through informed interactions and efficient deep learning queries. This course delves into scalable deployment, microservices, modern LangChain paradigms for dialog management, and practical application with advanced models, aiming at those with a solid grasp of LLMs, Python, and ideally some web engineering knowledge.
5. Introduction to AI in the Data Center
Duration: 5 hours
This course provides an understanding of Artificial Intelligence, including its applications, Machine Learning, and Deep Learning processes. It explains how training and inference operate in Deep Learning workflows. The course also covers the development and structure of GPUs, contrasting them with CPUs and highlighting their importance in AI advancements. Participants will learn about deep learning frameworks, the AI software stack, and how to deploy AI workloads in data centers, either on-premises or in the cloud. Additionally, it addresses the requirements for building multi-system AI clusters and the necessary considerations for infrastructure planning, such as servers, networking, storage, and tools.
These courses vary in duration, from as short as one hour to as long as eight hours, making it feasible for learners to complete a course in a single day if they can dedicate the time.
