# Action Items and Prerequisites

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To kick off an interactive and engaging learning journey, we've crafted a special exercise to ensure you make the most out of this course. We're thrilled to have you with us and want to guide you through a few simple steps to get started:

## :rocket: Action Items to Consider

### 1. Let's get you registered

* First things first, please ensure you're [registered on Unstop](https://unstop.com/workshops-webinars/pathway-challenge-tryst-iit-delhi-942498). It’s the gateway to our adventure together.
* Depending on your familiarity with LLMs and keeping an eye on the timeline, feel free to explore the 'Bonus Modules'. They're like the cherry on top – not required for your project or quizzes, but they sure can enrich your learning experience.

### **2. Show your support to the GitHub Repositories**

* Visit the [Pathway](https://github.com/pathwaycom/pathway) and [LLM App](https://github.com/pathwaycom/llm-app) GitHub repositories and give them your support with a star.
* Why does this matter? It’s more than just a click; it’s your way of cheering on the project and staying in the loop as things evolve. Got a question? The GitHub issues are your go-to spot.&#x20;

### 3. Join [Pathway's Discord Community](https://discord.gg/pathway) and Introduce Yourself

* **Your Action Item:** Become part of the vibrant Pathway Discord community, a hub for enthusiasts, creators, and some of the notable changemakers in the field of AI and Data.
* Make your first post in the **#introductions** channel.&#x20;
  * Please note, that the '**#introductions**' channel on Pathway's Discord is **NOT** specific to the bootcamps, and it includes some of the finest AI/Data practitioners whom you might want to collaborate with. While introducing yourself, please feel free to skip the bootcamp and focus on who you are as an engineer or your interests. You can consider sharing about your progress in the field, your background/projects, and what excites you. That's a great way to make a solid first impression – not in Pathway but in any open-source community.&#x20;
  * We have created an exclusive channel for this bootcamp, **i.e. #tryst-iitd-bcamp.** Please make sure you're asking all of your bootcamp-specific doubts in the same.&#x20;
  * **Pro Tip:** Immersing yourself in any vibrant open-source community not only enriches your learning experience but also opens up opportunities for networking and collaboration.

We're thrilled to have you with us and can't wait to see the contributions and growth you'll bring to this journey. Let's embark on this educational venture together with enthusiasm and curiosity!

## :rocket: Prerequisites for a headstart

For the majority of the bootcamp, these prerequisites aren't necessary. So, if you're an AI product manager or someone who isn't typically hands-on, you'll be just fine. However, as we approach the hands-on development phase towards the end of the bootcamp, these skills will become essential. That's why we're introducing them to you now, allowing you to familiarize yourself with them at your own pace before we dive into the more technical aspects.

1. **Python Proficiency:** A foundation in Python 3.11 is crucial. Here are some beginner-level resources to consider: [CodeChef](https://www.codechef.com/learn/course/python) | [Microsoft Trainings](https://learn.microsoft.com/en-us/training/paths/beginner-python/) | [Python.org](https://wiki.python.org/moin/BeginnersGuide/NonProgrammers).&#x20;
2. **Familiarize with Generative AI Tools:** Tools like Gemini, Anthropic's Claude 3 (yep, it's just released), Bing Search, or our dear ChatGPT can be invaluable for overcoming obstacles, rephrasing ideas, or basic code debugging. Try to use them a bit in your day-to-day lives.
3. **Explore Docker:** Docker simplifies the process of bundling your app and its necessities, making it portable and easy to share. It’s a powerful tool to standardize development environments and sidestep dependency issues – thus making it useful not just for LLM apps but open source development in general. Below are a few resources.
   * Beginner Blog on What is Docker: [Here](https://www.atlassian.com/microservices/microservices-architecture/docker)
   * Basic Tutorial on Dockerfile: [Here](https://youtu.be/0eMU23VyzR8)
   * Basic Tutorials on Docker Compose: [Part 1 using (Single Container)](https://youtu.be/600SC33F6Ag), [Part 2 (using 2 Containers)](https://youtu.be/WBqHr2kPc_A)
   * Blog on using ChatGPT to build an optimized Docker Image: [3-Minute Read](https://collabnix.com/when-chatgpt-meet-docker-for-the-first-time/)
4. **Know what stream data processing is:**&#x20;
   1. Gaining a very basic understanding of stream data processing and real-time data can be very beneficial, setting the stage for more advanced project ideas and development strategies even within the realm of LLMs. Here's a [basic blog](https://docs.google.com/document/d/17IwrPP9NQkYlITHvK04kW0DNcSpS7utACTzMF3cmmp4/edit?usp=sharing) to check out for starters.&#x20;
   2. Prof Abhilash Jindal (CSE, IIT Delhi) also took a session to explore the wonderful history beyond stream data processing. Check the kick-off session in the next module to watch the interactive session.

