Welcome to 7CS070 - Concepts and Technologies of AI! In this module, you will learn the fundamentals of artificial intelligence and how to create machine learning applications to tackle real-life problems. We will be focusing on two main concepts: regression and classification.

If you're new to this module, start here! We recommend that you go through each module in order, following the weekly schedule.

The module materials include:

• Reading assignments to help you understand the concepts and theories.
• Lectures or presentations to guide you through the main ideas and topics.
• Images to illustrate the concepts and make them easier to understand.
• Watching videos to show you how to use machine learning tools and techniques.
• Writing assignments to help you practice what you've learned.
• Discussion forums to ask questions, share ideas, and collaborate with your peers.
• Quizzes and tests to assess your understanding of the material.

All activities will be submitted digitally. Your primary modes of communication will be email, announcements, and discussion forums.

Here's the file structure for this module:

├── ASSIGNMENT
│   ├── Classification
│   │   └── Classification Assignment.ipynb
│   └── Regression
│       └── Regression Assignment.ipynb
├── Week 1
│   ├── Workshop 1.ipynb
│   └── Data.csv
├── Week 2
│   ├── Workshop 2.ipynb
│   └── Data.csv
├── Week 3
│   ├── Workshop 3.ipynb
│   └── Data.csv
└── README.md

The ASSIGNMENT directory contains the assignments for this module. You'll find two subdirectories:

• Classification: Here, you'll find the Jupyter notebook and HTML file for the classification assignment.
• Regression: This directory contains the Jupyter notebook and HTML file for the regression assignment.

The Week X directories contain the materials for each week of the module. Each week may include one or more of the following:

• Workshop X.ipynb: In this Jupyter notebook, you'll get hands-on practice with the tools and techniques covered in the module.
• Data .csv: This will contain the data used for the workshop.

To get started, clone this repository to your local machine:

git clone https://github.com/Rawlsy-py/7CS070_AI_Tech

Then, navigate to the directory and start working on the files:

cd 7CS070_AI_Tech
jupyter notebook

You can learn from my mistakes, please do not copy the code exactly and instead learn and develop from my experience.

If you want to learn more, reach out to me via the details on my profile page.

This repository is licensed under the GNU GPLv3 license.