Free Online Courses: Python

Course Description

This comprehensive Python course takes you from the very basics of writing your first “Hello, World!” script to building advanced applications and working on real-world projects. Through a structured sequence of lessons, you’ll learn fundamental programming concepts, data structures, object-oriented practices, and powerful libraries that form the backbone of Python’s versatility. Along the way, you’ll develop proficiency in essential skills such as debugging, testing, and managing environments so that you can write clean, efficient, and reliable code.

Beyond the core language topics, you’ll explore advanced features including functional programming, asynchronous execution, and web development with frameworks like Flask. You’ll also delve into data science workflows, covering NumPy, pandas, and data visualization with matplotlib and seaborn. Two capstone projects—one focusing on data scraping and analysis, and another on developing a functional web application—provide hands-on experience integrating everything you’ve learned into cohesive, practical solutions.

Course Objectives

By the end of the course, you should be able to:

1. Set up a Python development environment and run Python scripts confidently.

2. Understand and apply fundamental Python syntax, data types, and control structures.

3. Organize and manipulate data effectively using lists, dictionaries, sets, and other data structures.

4. Write reusable, modular code using functions, including advanced argument handling and recursion.

5. Implement object-oriented principles: define classes, use inheritance, and encapsulate data safely.

6. Handle files, manage exceptions, and debug programs using best practices.

7. Work with modules, packages, and virtual environments to structure and share your Python projects.

8. Explore functional programming concepts, decorators, generators, and context managers for efficient coding.

9. Read and write data in common formats such as JSON and CSV, including web data retrieval via APIs.

10. Automate tasks, build command-line applications, and schedule repetitive processes.

11. Develop simple web applications with Flask and integrate databases for persistent data storage.

12. Perform data analysis and visualization with NumPy, pandas, and plotting libraries.

13. Write and maintain unit tests, apply mocking, and follow code style conventions for robust, maintainable projects.

14. Implement concurrency and asynchronous programming for scalable I/O-bound solutions.

15. Complete capstone projects that demonstrate real-world skills in data scraping, analysis, and web app development.

Table of Contents

• Introduction and Setup

• Running Python Scripts and The REPL

• Basic Python Syntax and Hello World

• Variables and Data Types

• Numeric Types and Operations

• Strings and Text Manipulation

• Boolean Logic and Comparison Operators

• Conditional Statements (if/elif/else)

• Loops and Iteration (for and while)

• Lists and Tuples (Sequence Data Structures)

• Dictionaries (Key-Value Pairs)

• Sets and Set Operations

• Defining and Calling Functions

• Function Arguments and Return Values

• Variable Scope and Lifetime

• Recursion

• Exception Handling (Try/Except)

• Debugging Techniques and Problem Solving

• File Input and Output

• Modules and the Standard Library

• Packages and Project Structure

• Virtual Environments and Package Management

• Introduction to Object-Oriented Programming (OOP)

• Classes and Objects in Python

• Inheritance and Polymorphism

• Advanced OOP – Encapsulation and Special Methods

• Iterators and Generators

• Decorators and Higher-Order Functions

• Context Managers (The with Statement)

• Functional Programming in Python

• Regular Expressions (Regex)

• Working with HTTP and APIs (Requests)

• Data Formats: JSON and CSV

• Web Scraping with Python (BeautifulSoup)

• Building Command-Line Applications (argparse)

• Automating Tasks with Python

• Working with Databases (SQLite)

• Introduction to Web Development with Flask

• Unit Testing and Mocking

• Code Style and Best Practices

• Packaging and Distribution of Python Projects

• Numerical Computing with NumPy

• Data Analysis with Pandas

• Data Visualization with Matplotlib and Seaborn

• Concurrent Programming in Python

• Asynchronous Programming (asyncio)

• Capstone Project: Data Scraping and Analysis

• Capstone Project: Web Application Development