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Generative AI has become mainstream over the last several months, and it’s only going to get better. So how do you upskill and stay current on all the recent advances?
But here’s the good news: with all the recent advances there’s also been an uptick in the number of high-quality free learning resources available. This is a compilation of free AI courses from NVIDIA—the NVIDIA Deep Learning Institute—to get you up to speed on AI topics and start building impactful solutions.
So let’s go over the courses and what they cover!
Generative AI Explained
Generative AI Explained is a beginner-friendly introduction to generative AI fundamentals to get your feet wet. This course will introduce you to the following topics:
- Generative AI and how Generative AI works
- Generative AI applications
- Challenges and opportunities in Generative AI
By the end of this course, you’ll have gained a good understanding of what generative AI is, how it works, and how you can use it.
Link: Generative AI Explained
Building a Brain in 10 Minutes
Large language models are currently super popular and super helpful. However, before you dive into LLMs, a basic understanding of how neural networks work is necessary.
Building a Brain in 10 Minutes is an introduction to building a neural network with references to biological inspirations that guide the neural network architecture.
To make the most out of this course, you have to be comfortable with programming in Python and regression models. This short course will help you learn the following:
- How neural networks learn from data
- The math behind the neuron and the working of a neural network
Link: Building a Brain in 10 Minutes
Augment Your LLMs Using Retrieval Augmented Generation
Whenever you want to build applications that use LLMs, you’d also use Retrieval Augmented Generation (RAG). With RAG, you can build LLM apps on domain-specific data, mitigate LLM hallucinations, and much more.
The Augment Your LLMs Using Retrieval Augmented Generation course will teach you how to build a RAG pipeline that uses information retrieval and response generation. It’ll help get a good grasp of the basics of RAG and the RAG retrieval process.
Link: Augment Your LLMs Using Retrieval Augmented Generation
Building RAG Agents with LLMs
Once you’re familiar with how RAG works from the previous course, you can take the Building RAG Agents with LLMs course to explore RAG in much greater detail by building end-to-end LLM systems.
To ace this course, it’ll be helpful to have intermediate programming experience with Python and some programming experience with PyTorch. In this course, you’ll explore designing LLM pipelines and use tools like Gradio, LangChain, and LangServe. You’ll also get to experiment with embeddings, models, and vector stores for retrieval.
Link: Building RAG Agents with LLMs
Wrapping Up
I hope you found this comprehensive list of free AI courses from the NVIDIA Deep Learning Institute helpful.
But if you are interested in exploring LLMs and Generative AI further, here are a couple of articles you may find useful:
So happy learning and coding!
Bala Priya C is a developer and technical writer from India. She likes working at the intersection of math, programming, data science, and content creation. Her areas of interest and expertise include DevOps, data science, and natural language processing. She enjoys reading, writing, coding, and coffee! Currently, she’s working on learning and sharing her knowledge with the developer community by authoring tutorials, how-to guides, opinion pieces, and more. Bala also creates engaging resource overviews and coding tutorials.
