Python-refresh

Welcome to Python-refresh – my personal repository to refresh and sharpen my Python skills in preparation for my upcoming MSc course in Artificial Intelligence (starting this September). This project is designed to help me (and anyone interested) revisit the core concepts of Python, explore intermediate topics, and build practical projects that bridge theory with real-world applications.

Table of Contents

• Motivation
• Learning Objectives
• Project Structure
• How to Use This Repository
• Resources
• License

Motivation

As I embark on my MSc journey, I want to ensure that my Python foundation is rock solid. This repository is my space for:

• Revisiting Python basics and core syntax.
• Practicing intermediate concepts like functions, object-oriented programming, and module usage.
• Experimenting with data manipulation and visualization using libraries such as NumPy, Pandas, and Matplotlib.
• Exploring introductory machine learning and AI concepts relevant to my MSc coursework.

Learning Objectives

The refresh plan is structured into several phases:

1. Python Fundamentals

   • Review basic syntax, data types, variables, loops, and conditionals.
   • Solve coding challenges to rebuild muscle memory.

2. Intermediate Python

   • Deep dive into functions, error handling, and object-oriented programming.
   • Work with modules and packages to organize code effectively.

3. Scientific Computing & Data Handling

   • Explore NumPy for numerical operations.
   • Use Pandas for data manipulation and Matplotlib/Seaborn for visualization.

4. Introduction to Machine Learning

   • Get started with scikit-learn and basic ML algorithms.
   • Understand how Python is applied in AI systems.

5. Capstone Projects

   • Integrate learned concepts by building mini-projects that simulate real-world scenarios.
   • Document challenges, solutions, and insights gained throughout the process.

Project Structure

The repository is organized into folders representing different phases of the refresh plan:

• 01_Fundamentals/ – Basic syntax, data types, loops, and conditionals.
• 02_Intermediate/ – Functions, OOP, modules, and error handling.
• 03_DataScience/ – Exercises using NumPy, Pandas, and visualization libraries.
• 04_MachineLearning/ – Introductory projects and experiments with ML concepts.
• 05_Capstone/ – End-to-end projects integrating various Python skills.

Each folder contains code samples, exercises, and personal notes documenting my progress and any challenges encountered.

How to Use This Repository

• Clone the Repository:

  git clone https://github.com/jozsefKecskesi/Python-refresh.git
  

Resources

• Jupyter Notebooks
• Google Colabs
• GitHub Workspaces

License

Free to use for any purpose, including commercial. Use it under your own responsibility, but freely.