Python Course - Lecture by Mosh
Introduction
- Python is a versatile language used for automation, AI, application development, etc.
- Course will cover core concepts and involve building three projects.
- Project 1: Building a website for a grocery store using Django.
- Project 2: Predicting music preferences using machine learning.
- Project 3: Automating data processing tasks (e.g., spreadsheets).
Setting Up Python and PyCharm
- Install Python from python.org.
- Install PyCharm from jetbrains.com/pycharm.
- Ensure correct setup with Python 3.x.
Writing Your First Python Program
- Create a new project in PyCharm.
- Create a Python file and write a simple
print function to display a message.
- Running the program displays the output in the terminal.
Basics of Python Programming
Data Types
- Integers, floats, strings, and booleans.
- Lists for storing collections of data.
- Example operations: sorting, adding, removing elements.
Variables
- Used to store data temporarily.
- Assign using
= (e.g., price = 10).
Operators
- Arithmetic:
+, -, *, /, //, %, **.
- Augmented assignments:
+=, -=, *=, /=.
- Operator precedence and using parentheses to control order.
Control Flow
Conditional Statements
if, elif, and else for decision-making in code.- Example: Checking temperature to print messages.
Logical Operators
and, or, and not for combining boolean conditions.- Example: Loan eligibility based on income and credit.
Comparison Operators
>, <, >=, <=, ==, != for comparing values.- Example: Validating user input length.
Loops
while loops for repeated execution based on a condition.for loops for iterating over collections like lists.- Nested loops for complex iterations, e.g., generating coordinates.
- Example: A guessing game using
while loops.
Functions
- Define using
def keyword.
- Take parameters and optional return values.
- Example: A function to greet user by name.
- Positional and keyword arguments in function calls.
- Importing and using functions across multiple files (modules).
Modules and Packages
- Organize related code into separate files (modules) and directories (packages).
- Example: A module
utils.py with utility functions.
- Import modules using
import and from ... import ... syntax.
Error Handling
- Use
try, except blocks to handle exceptions gracefully.
- Example: Handling division by zero and invalid input errors.
Classes and Object-Oriented Programming
- Define classes using
class keyword.
- Example: A
Point class with methods for moving and drawing.
- Constructors (
__init__) for initializing objects.
- Inheritance for reusing code across related classes.
Working with Files and Directories
- Use built-in modules like
pathlib for file operations.
- Example: Creating, deleting directories, and searching files.
Automation with Python
Project: Processing Spreadsheets
- Use
openpyxl to read and write Excel files.
- Automate tasks like updating prices and adding charts.
Machine Learning with Python
Introduction
- Overview of machine learning (ML) concepts and applications.
- Steps in an ML project: Import data, clean data, split data, train model, make predictions, evaluate model.
Tools and Libraries
- Jupyter for interactive coding and data visualization.
- Libraries:
numpy, pandas, matplotlib, scikit-learn.
- Setting up Anaconda for a comprehensive Python distribution.
Project: Music Recommendation System
- Import and explore dataset using
pandas.
- Prepare data by splitting into input and output sets.
- Train a machine learning model with
scikit-learn.
- Evaluate model accuracy and fine-tune as needed.
Creating Web Applications with Django
Introduction to Django
- Django is a high-level Python web framework.
- Used for building secure and scalable web applications.
Setting Up Django
- Install Django and create a new Django project.
- Use
manage.py for starting the server and managing the project.
- Basic project structure: settings, URLs, etc.
This document provides a broad overview and can be used as a reference and guide for further detailed study of each topic.