> For the complete documentation index, see [llms.txt](https://kdag-iit-kharagpur.gitbook.io/realtime-llm/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://kdag-iit-kharagpur.gitbook.io/realtime-llm/get-started-with-the-bootcamp.md).

# Get started with the Bootcamp!

We are about to embark on a short but exciting journey into the realm of Large Language Models (LLMs)!

<figure><img src="/files/sCzXFpxkQNfByouZ7qjw" alt=""><figcaption></figcaption></figure>

This bootcamp, offered at no cost as a cohort-based course, is designed to be your all-encompassing tutorial for mastering and creating RAG (Retrieval-Augmented Generation) applications, leveraging the capabilities of Large Language Models (LLMs) and live/real-time data streams.

If this concept seems daunting, that's perfectly okay. By the time you complete this bootcamp, not only will you have a deep appreciation for these advanced techniques and technologies, but you'll also be equipped to develop a significant open-source project independently!

:star: **Please make sure** to finish your [registration on Unstop](https://unstop.com/workshops-webinars/spring-of-realtime-llms-bootcamp-iit-kharagpur-917873?lb=Yxt5XWS) and star the GitHub repositories mentioned below. It's your way to support our work and be a part of the Pathway community. Besides, we will be referring back to these resources throughout the course.

* <https://github.com/pathwaycom/pathway>
* <https://github.com/pathwaycom/llm-app>

**This course is offered as a collaborative initiative** by the Kharagpur Data Analytics Group at the Indian Institute of Technology Kharagpur (IIT KGP) in collaboration with Pathway, a French research company and the makers of the world's fastest data processing engine.

**In the Next Module:**\
You will explore into the structure of the course, get acquainted with its creators, understand what you can gain from participating, and understand your role as a learner.