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Action Items and Prerequisites

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:

🚀 Action Items to Consider

1. Let's get you registered

  • First things first, please ensure you're registered. It’s the gateway to our adventure together.
  • It might be a good idea to tag along a couple of your learning buddies with whom you can set learning goals for this bootcamp.
  • Feel free to explore the 'Bonus Modules' as and when you come across them within the coursework. They're like the cherry on top – not required for your project or quizzes, but they sure can enrich your foundational understanding of things.

2. Show your support to the GitHub Repositories

  • Visit the Pathway and the LLM App Templates 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.

3. Join Pathway's Discord Community 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.
    • 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 as many community members might not even understand what you're referring to when you mention bootcamps. :) You can, however, 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.
    • We create exclusive channels for each university's bootcamp on our Discord server. For example, #📚gdsc-ucdavis-bootcamp for UC Davis. Please ensure you ask all your bootcamp-related questions in your university's dedicated channel.
    • 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!

🚀 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 | Microsoft Trainings | Python.org.
  2. Familiarize with Generative AI Tools: Tools like Gemini, Anthropic's Claude 3, 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.\
  4. Get to know about deployment: Deployment is the process of making a software application or project available for use, usually by transferring it from a developer's computer to a server or cloud environment. This allows users to access and interact with the application over the internet or within a network. You can refer to these resources.
    • Concept explained in a 1.5-minute video: Here
    • An overview video for AWS Fargate, a containerless deployment service: Here
    • Pathway tutorials about deployment in AWS, Google Cloud, and Azure.
  5. Know what stream data processing is:
    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 to check out for starters.
    2. Prof Abhilash Jindal (CSE Department at IIT Delhi) also took a session to explore the wonderful history beyond stream data processing. You can find their session slides here and the recording on DevClub IIT Delhi's YouTube channel.