Intro to Python Course

Lesson 1 • Python Syntax Fundamentals

Learn indentation rules, comments, and statement structure that define valid Python code. Correct syntax habits prevent the most common beginner errors.

Lesson 2 • Using the Python Interpreter

Interact with Python through the interactive shell to execute expressions immediately. This builds intuition for how Python evaluates code line by line.

Lesson 3 • Writing and Running Scripts

Create .py files and execute them from the command line to produce repeatable programs. Students transition from one-off commands to structured code files.

Lesson 1 • Arithmetic and Assignment Operators

Apply arithmetic operators and shorthand assignment operators to compute results. These operators form the computational core of most Python programs.

Lesson 2 • Comparison and Logical Operators

Evaluate conditions using comparison and logical operators that return boolean values. These operators drive decision-making in control flow structures.

Lesson 3 • Core Data Types

Distinguish integers, floats, strings, and booleans as Python's primary data types. Choosing the correct type ensures accurate data representation and operations.

Lesson 4 • Variables and Assignment

Assign values to named variables and follow Python naming conventions. This skill is the basis for storing and reusing data throughout a program.

Lesson 1 • Loop Control and Patterns

Apply break, continue, and else clauses on loops to implement common iteration patterns. These tools give precise control over complex looping scenarios.

Lesson 2 • while Loops

Repeat a block of code as long as a condition remains true using while loops. Students learn to control iteration and avoid infinite loops.

Lesson 3 • for Loops and Ranges

Iterate over sequences and numeric ranges using for loops and the range() function. This section connects looping to Python's iterable data model.

Lesson 1 • Defining and Calling Functions

Use the def keyword to create named functions and invoke them with arguments. Functions are the primary mechanism for structuring and reusing logic.

Lesson 2 • Return Values and Scope

Return computed results from functions and understand how variable scope limits access. Scope rules prevent naming conflicts in larger programs.

Lesson 3 • Parameters and Arguments

Pass data into functions through positional, keyword, and default parameters. Flexible parameter design makes functions adaptable to many use cases.

Lesson 4 • Lambda Functions and Built-ins

Write concise anonymous functions with lambda and leverage Python's built-in functions. These tools accelerate common tasks without requiring custom function definitions.

Lesson 1 • List Methods and Mutation

Modify lists in place using append, insert, remove, and sort methods. Mutation methods enable dynamic data management without creating new objects.

Lesson 2 • Sets and Set Operations

Use sets to store unique elements and perform mathematical set operations efficiently. Sets are ideal for deduplication and membership testing at scale.

Lesson 3 • List Comprehensions

Build new lists from existing iterables using concise comprehension syntax. Comprehensions replace verbose loops and improve code readability.

Lesson 4 • Tuples and Immutability

Create tuples as fixed, ordered sequences and understand when immutability is advantageous. Tuples protect data integrity and enable use as dictionary keys.

Lesson 1 • Dictionary Methods and Iteration

Iterate over keys, values, and items using dictionary methods and for loops. These techniques enable processing every entry in a dictionary systematically.

Lesson 2 • String Slicing and Parsing

Extract substrings using slicing and parse structured text into usable data. These skills bridge raw text input and structured program data.

Lesson 3 • String Methods and Formatting

Transform and query strings using built-in methods and format output with f-strings. String manipulation is essential for user-facing output and data parsing.

Lesson 1 • Custom Exceptions and Validation

Define custom exception classes and validate input to enforce program correctness. Custom exceptions communicate domain-specific errors clearly to other developers.

Lesson 2 • Working with CSV Files

Parse and write comma-separated data using Python's csv module for tabular data. CSV handling is a foundational skill for data exchange between applications.

Lesson 3 • Reading and Writing Text Files

Open files with the open() function and read or write content using file objects. File I/O enables programs to persist and share data beyond a single run.

Lesson 4 • Exception Handling with try/except

Catch and handle runtime exceptions using try, except, else, and finally blocks. Proper error handling prevents crashes and provides meaningful feedback to users.

Lesson 1 • Modules, Packages, and OOP Design

Organize classes into modules and packages and apply basic OOP design principles. Proper organization scales object-oriented code across multi-file projects.

Lesson 2 • Inheritance and Method Overriding

Create subclasses that inherit and extend parent class behavior through method overriding. Inheritance promotes code reuse and models hierarchical real-world relationships.

Lesson 3 • Encapsulation and Properties

Control attribute access using private conventions and property decorators. Encapsulation protects internal state and enforces valid data through controlled interfaces.

Lesson 4 • Classes and Objects

Define classes with attributes and methods, then instantiate objects from them. Classes are blueprints that encapsulate related data and behavior together.