Python Course Summary

Introduction

• Instructor: Mosh Hamedani
• Python is popular for automation, AI, applications, and websites (e.g., Instagram, Dropbox).
• Course outline: Core concepts + 3 projects

Course Projects

1. Grocery Store Website: Using Django framework.

   • Homepage displays products and admin area for stock management.

2. Machine Learning:

   • Predict music preferences based on profile (similar to YouTube recommendations).

3. Automation:

   • Automate processing thousands of spreadsheets quickly.

Course Structure

• Designed for all ages, suitable for beginners.
• Exercises included to build confidence.
• Instructor has 20 years of experience, taught over 3 million people.

Installing Python

1. Go to python.org.
2. Click on downloads, download the latest version (e.g., Python 3.7.2).
3. Install using installer, ensure to add Python to PATH (Windows).

Installing Code Editor

• Recommended: PyCharm
  • IDE with additional features for Python development.
  • Download from JetBrains.
  • Use Community Edition (free).

Your First Python Program

• Create a new project in PyCharm, create app.py file.
• Write a print statement to display your name.
• Run the program via the Run menu or shortcuts.

Variables, Data Types, and Input

• Variables: Used to store data (price = 10, rating = 4.9, etc.).
• Data Types: Integers, floats, strings, and booleans.
• User Input: Use input() to receive input from users.

Control Flow and Functions

• If Statements: Used for conditional execution.
• Loops: for and while loops to iterate over data.
• Functions: To encapsulate code for reusability.

Lists and Dictionaries

• Lists: Ordered collections of items.
  • Access items using indices, slicing.
  • Common methods: append(), remove(), sort(), etc.
• Dictionaries: Key-value pairs for storing data.
  • Access values using keys and handle non-existing keys with get() method.

Object-Oriented Programming

• Classes: Define new types and encapsulate data and methods.
  • Constructor: __init__ method for initializing object attributes.
  • Inheritance: Mechanism for reusing code in subclasses.

Modules and Packages

• Modules: Organize code into separate files (e.g., utils.py).
• Packages: Directories containing multiple modules (e.g., ecommerce).
• Standard Library: Built-in modules for common tasks (e.g., random, datetime).

Exception Handling

• Use try and except to handle errors gracefully.
• Anticipate errors, keep the program running without crashing.

Working with Data

• Use libraries like Pandas for data manipulation.
• Load data from CSV files, process data cleaning, and perform analysis.

Machine Learning Overview

• Process involves: Data collection, cleaning, splitting, model training, and evaluation.
• Use libraries like Scikit-learn for machine learning algorithms.

Final Thoughts

• Python is a powerful tool for automation, data analysis, and web development.
• Encouraged to explore further with projects and practical applications.