update index of docs

docs/index.md

@@ -1,17 +1,29 @@
 # Welcome to the Zero to Mastery Data Science and Machine Learning Bootcamp!
 
-This documentation is a work in progress and will be updated rapidly over the next few weeks.
+This webpage contains all of the materials for the Zero to Mastery Data Science and Machine Learning Bootcamp.
 
-In the meantime, check out the following:
+## Quick Links
 
 * 📚 Get the course materials on the [course GitHub](https://github.com/mrdbourke/zero-to-mastery-ml/)
 * 🎥 Watch the [first 10 hours of the course on YouTube](https://youtu.be/r67SfaiYaDI?ref=mrdbourke.com)
 * 🤓 [Read more](https://www.mrdbourke.com/mlcourse/?ref=mrdbourke.com) on the course page
 * 💻 [Sign up to the course on Zero to Mastery](https://dbourke.link/ZTMmlcourse?ref=mrdbourke.com) and start coding
 
-**Currently working on:** Updating the [Dog Vision project](https://dev.mrdbourke.com/zero-to-mastery-ml/end-to-end-dog-vision-v2/) (classifying images of dogs with computer vision) for 2024.
+## Contents
 
-Best, 
+| **Resource** | **Description** |
+|--------------|-----------------|
+| [A 6 step framework for approaching machine learning projects](https://dev.mrdbourke.com/zero-to-mastery-ml/a-6-step-framework-for-approaching-machine-learning-projects/) | A guideline for different kinds of machine learning projects and how to break them down into smaller steps. |
+| [Introduction to NumPy](https://dev.mrdbourke.com/zero-to-mastery-ml/introduction-to-numpy/) | NumPy stands for Numerical Python. It's one of the most used Python libraries for numerical processing (which is what much of data science and machine learning is). | 
+| [Introduction to pandas](https://dev.mrdbourke.com/zero-to-mastery-ml/introduction-to-pandas/) | pandas is a Python library for manipulating and analysing data. You can imagine pandas as a programmatic form of an Excel spreadsheet. |
+| [Introduction to Matplotlib](https://dev.mrdbourke.com/zero-to-mastery-ml/introduction-to-matplotlib/) | Matplotlib helps to visualize data. You can create plots and graphs programmatically based on various data sources. |
+| [Introduction to Scikit-Learn](https://dev.mrdbourke.com/zero-to-mastery-ml/introduction-to-scikit-learn/) | Scikit-Learn or sklearn is full of data processing techniques as well as pre-built machine learning algorithms for many different tasks. |
+| [Introduction to TensorFlow/Keras and Deep Learning](https://dev.mrdbourke.com/zero-to-mastery-ml/end-to-end-dog-vision-v2/) | TensorFlow/Keras are deep learning frameworks written in Python. Originally created by Google and are now open-source. These frameworks allow you to build and train neural networks, one of the most powerful kinds of machine learning models. In this section we'll learn about deep learning and TensorFlow/Keras by building Dog Vision 🐶👁️, a neural network to identify dog breeds in images. |
+| [Communicating your work](https://dev.mrdbourke.com/zero-to-mastery-ml/communicating-your-work/) | One of the most important parts of machine learning and any software project is communicating what you've found/done. This module takes the learnings from the previous sections and gives tips and tricks ons how you can communicate your work to others. |
+
+If you have any questions, leave an issue/discussion on the [course GitHub](https://github.com/mrdbourke/zero-to-mastery-ml/).
+
+## Author
 
 [Daniel Bourke](https://www.mrdbourke.com)