# Course Syllabus and Timelines

By the end of this course, you will:

* Be proficient in developing LLM-based applications for production applications from day 0.
* Have a clear understanding of LLM architecture and pipeline.
* Be able to perform prompt engineering to use generative AI tools such as ChatGPT.
* Create an open-source project on a real-time stream of data or static data.

## Module Release Timelines and the Coursework:



<table data-view="cards"><thead><tr><th>Module</th><th>Topics</th></tr></thead><tbody><tr><td><strong>1 – Basics of LLMs</strong></td><td><ul><li>What is generative AI and how it's different</li><li>Understanding LLMs</li><li>Advantages and Common Industry Applications</li><li>Bonus section: Google Gemini and Multimodal LLMs</li></ul><p>---<br><br>Release date: 31st March '24</p></td></tr><tr><td><strong>2 – Word Vectors</strong></td><td><ul><li>What are word vectors and word-vector relationships?</li><li>Role of context</li><li>Transforming vectors in LLM responses</li><li>Overview of Transformers Architecture</li><li>Bonus Resource: Transformers Architecture, Self-attention, Multi-head attention, and Vision Transformers</li></ul><p>---<br><br>Release date: 2nd April '24<br></p></td></tr><tr><td><strong>3 – Prompt Engineering</strong></td><td><ul><li>Introduction and in-context learning</li><li>Best practices to follow: Few Shot Prompting and more</li><li>Token Limits</li><li>Prompt Engineering Exercise (Ungraded)</li></ul><p>--</p><p></p><p>Release date: 4th April '24<br><br>---<br><br>Pushed by a day.</p></td></tr><tr><td><strong>Refresher Module</strong></td><td><ul><li>Overview of learnings so far sent over registered email address. </li><li>Release of bootcamp keynote session(s).</li></ul><p></p></td></tr><tr><td><strong>4 – RAG and LLM Architecture</strong></td><td><ul><li>Introduction to RAG</li><li>LLM Architecture Used by Enterprises</li><li>RAG vs Fine-Tuning and Prompt Engineering</li><li>Key Benefits of RAG for Realtime Applications</li><li>Bonus: Similarity Search for Efficient Information Retrieval</li><li>Bonus: Use of LSH + kNN and Incremental Indexing</li><li>Bonus: Forgetting in LLMs and Stream Data Processing (archived live interactions) </li></ul><p>--<br><br>Release date: 8th April '24 (Revised)</p></td></tr><tr><td><strong>5 – Hands-on Development of Realtime LLM Applications</strong></td><td><ul><li>Installing Dependencies and Pre-requisites</li><li>Building a Dropbox RAG App using open-source </li><li>Building Realtime Discounted Products Fetcher for Amazon Users</li><li>Building RAG applications with local models</li><li>Leveraging Pathway with LlamaIndex/Langchain (Bonus)</li><li>Problem Statements for Projects</li><li>Project Submission</li></ul><p>--<br><br>Release date: 10th April '24 (Revised)</p></td></tr><tr><td><strong>6 – Project Development</strong></td><td><p></p><ul><li>Problem Statements Release for the Projects</li><li>Online Office Hours</li><li>Projects Submission</li><li>Project Feedback (after the submissions deadline)</li></ul><p>--</p><p></p><p>Release date: 12–21st April '24</p></td></tr></tbody></table>

### Note:&#x20;

Once the problem statements and the hands-on development module are released on the 10th of April 2024, the project submissions will be open till **21st of April 2024, Monday 12 am CEST.**

### What are Bonus Sections/Resources?&#x20;

Throughout the bootcamp, you'll see some modules or links labeled as bonus resources. These are **not compulsory** for building a project by the end of the bootcamp or attempting the quizzes.

Nonetheless, they are relevant resources that could enhance your understanding, although they might require additional prerequisites. Depending on **your starting point** and the pace you're progressing through the bootcamp, you can explore or park these bonus materials.



