Python Beginner Course

Welcome to the Python Beginner Course, where you'll dive into basic data structures, conditional statements, loops, and more.

In this course, you'll master fundamental data structures in Python such as dictionaries, lists, sets, and tuples. These structures are crucial for organizing and manipulating data effectively in your Python programs.

📚 Course Contents:

📋 Lists in Python

• Lists are ordered collections of items that allow duplicates and are mutable.
• Operations:
• 🆕 Creating lists
• 🔍 Accessing elements
• ✂️ Slicing lists
• ✏️ Modifying lists
• 🛠️ List methods

📦 Tuples

• Tuples are ordered collections of items that are immutable.
• Operations:
• 🆕 Creating tuples
• 🔍 Accessing elements
• ✏️ Modifying tuples (indirectly, by creating new tuples)

🔑 Dictionaries

• Dictionaries are unordered collections of key-value pairs.
• Operations:
• 🆕 Creating dictionaries
• 🔍 Accessing elements by key
• ✏️ Adding and modifying elements
• 🛠️ Dictionary methods

🔗 Sets

• Sets are unordered collections of unique elements.
• Operations:
• 🆕 Creating sets
• ➕ Adding and ➖ removing elements
• ⚙️ Set operations: union, intersection, difference, symmetric difference

🗺️ Road Map:

Python Roadmap

🛠️ Prerequisites:

• Basic Python syntax and control structures (`if` statements, loops, functions).
• Python installed on your computer. You can download Python from here.

🚀 Getting Started:

1. Clone or download this repository to your local machine.
2. 🖥️ Clone using this command: git clone https://github.com/hasindunagolla/Python-Begginer-Course.git
3. Navigate to the directory where you've saved the course files.
4. Open your preferred Python IDE or text editor.
5. Start exploring the course content! Each section is organized in separate Python files.

📖 Further Resources:

• 📝 Python documentation: docs.python.org
• 📘 Real Python: realpython.com
• 📚 Python Data Structures and Algorithms by Benjamin Baka: Packt Publishing

📦 Installation:

1. Ensure you have Python installed on your computer. You can download it from here.
2. Navigate to the directory where you've saved the course files.
3. Create a virtual environment to manage your project dependencies (recommended):

python -m venv .venv

4. Activate the virtual environment:
• On Windows:

  .venv\Scripts\activate

• On macOS/Linux:

  source .venv/bin/activate

5. Install the required packages for data visualization using pip:

pip install matplotlib numpy

6. Start exploring the course content! Each section is organized in separate Python files.

🎉 Happy coding!