# Timelines and Structure

While most educators of this coursework are professionals with extensive backgrounds in professional and academic research, the focus of this course extends beyond traditional AI research. A key aspect of this course is its emphasis on building real-time Retrieval Augmented Generation (RAG) applications. This approach addresses two significant challenges in the industry that even skilled professionals find complex: leveraging Generative AI in production and developing real-time solutions.

Upon completing the course, you will not only gain insights into creating real-world, open-source LLM applications using RAG and real-time data but also develop a meaningful project of your own. This presents a unique chance to delve into and master a technically challenging yet highly rewarding upcoming field of technology.

### Course Structure: Live or Recorded?

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Short answer – mostly recorded. The course is crafted with a hybrid learning approach in mind. Most content is provided via recorded sessions, offering the flexibility to learn at your own pace. Additionally, if and when there will be interactive live sessions, [registered participants](https://lu.ma/llm23) will receive timely notifications.

This format balances self-paced learning with the dynamism of real-time interactions, ensuring a comprehensive educational experience without disrupting your professional or personal commitments.

### Introductory Session Recording (Optional)&#x20;

If you couldn't attend the kick-off session of the bootcamp live, you have the option to watch the 30-minute recorded interaction below.&#x20;

However, reading the course introduction is highly recommended. If you prefer, you can first read the course introduction and then return to the kick-off session's video if you have any questions or need further clarification.&#x20;

{% embed url="https://youtu.be/l6Cqg_etUl0" %}

### Bootcamp Completion and Rewards

To complete the bootcamp, you must complete all the quizzes within the specific deadlines and complete the project.

**For the course's project,** you will create and publish a novel GitHub project, utilizing open-source RAG frameworks to tackle real-world challenges. Criteria for bootcamp completion and eligibility for the top 9 prizes will be detailed as we progress towards project submission.&#x20;

However, it's worth noting that successful completion comes with its share of exciting rewards:

* **All graduates** receive Certificates, T-shirts, and swag.
* **Top 9 graduates** win XBOX controllers, phone camera lenses, and JBL waterproof speakers.

### Registration and Timelines

Register soon at [https://lu.ma/llm23-guwahati](https://lu.ma/llm23-guwahati); the deadline is December 13, 2023.&#x20;

The 3-week bootcamp is structured as follows:

* First 1-1.5 weeks: Focus on learning prerequisites and building a solid foundation.
* Final 2 weeks: Dedicated to hands-on development.

The modules will be released gradually.&#x20;

#### A Word of Advice

If this is your first foray into building a real-world AI application, be prepared for challenges in problem selection, data integration, and leveraging foundational LLM knowledge. Early engagement is key to overcoming these hurdles.

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