📘 ST2195 Programming for Data Science - Notes & Exercises

⚠️ DISCLAIMER: This repository is a personal collection of study materials and is not affiliated with, endorsed by, or connected to the University of London or the London School of Economics in any way. All content is created and maintained independently by students for educational purposes only.

Welcome to the ST2195 Programming for Data Science repository! This repository contains my notes, exercises, programs, and other materials related to the module. The content is structured based on the various blocks covered in the class, aiming to provide a comprehensive overview and hands-on practice in data science programming.

🗂 Course Overview

The ST21955 module is divided into the following blocks:

• Block 1: Introduction to Data Science 📊
• Block 2: Data 🗄️
• Block 3: Introduction to Relational Database Management Systems 🗃️
• Block 4: Programming Concepts 💻
• Block 5: Variables, Mutability and Aliasing in Python and R 🔧
• Block 6: Introduction to Data Wrangling 🛠️
• Block 7: Exploratory Analysis and Data Visualisation 🔍
• Block 8: Graphics and Data Visualisation in Python 📊
• Block 9: Machine Learning Frameworks 🤖
• Block 10: Introduction to Software Development 🛠️

📂 Repository Structure

The repository is organized into folders named after each block of the module. Each block contains:

• Notes 📝 - Detailed notes on the concepts covered.
• Example Code 💻 - Code snippets illustrating key programming concepts and techniques.
• Exercises 🏋️ - Practice exercises to reinforce learning.

This structure is designed to help you navigate the course material block-by-block.

📝 How the Module Will Be Assessed

This module is assessed through:

• Individual Case Study Coursework (50%) 📝 - A project-based assessment focusing on applying the concepts learned.
• Final Examination (50%) 🧑‍🎓 - A three-hour and fifteen-minute closed-book written exam covering key topics from the course.

Please refer to the official course syllabus for detailed assessment criteria and deadlines.

📚 Usage

Feel free to browse through the notes and exercises for reference. These materials can aid in your study and understanding of the course content.

🤝 Contribution

If you are also taking the ST2195 module and want to contribute, follow these simple steps:

1. Fork this repository by clicking the "Fork" button in the top-right corner of this page to create your own copy.
2. Clone your fork to your local machine using:

   git clone https://github.com/moebqr/ST2195-Programming-for-Data-Science.git

3. Create a new branch for your changes:

   git checkout -b your-branch-name

4. Add your changes (notes, exercises, code) to the appropriate block folder, then commit and push:

   git add .
   git commit -m "Your descriptive message"
   git push origin your-branch-name

5. Create a Pull Request on GitHub from your forked repository. Click "New Pull Request" and submit your changes for review.

Feel free to ask questions if you get stuck—contributing is a learning process!

All contributions should be directly relevant to the ST2195 Programming for Data Science module.

📜 Copyright Notice

All notes and content within this repository are © Mohamed Alderazi, 2024. Unauthorized reproduction, distribution, or use of these materials without explicit permission is prohibited.

📄 License

This repository is shared for educational purposes only. Please respect the copyright and contribution guidelines.