Python Computer Language Course

Lesson 1 • Basic Input, Output, and Formatting

Teaches print(), input(), and string formatting techniques. Connects syntax knowledge to interactive, user-facing programs.

Lesson 2 • Variables, Data Types, and Literals

Explains dynamic typing, built-in scalar types, and literal syntax. Students gain the ability to store and label data correctly.

Lesson 3 • Installing Python and Development Tools

Covers Python interpreter installation, version selection, and IDE setup. Provides the technical foundation every subsequent coding exercise depends on.

Lesson 4 • Core Syntax and Code Structure

Introduces indentation rules, comments, and statement structure. Ensures students write syntactically valid code from the first exercise.

Lesson 1 • For Loops and Iteration

Introduces for loops over sequences and the range() function. Builds the iteration skills needed for all collection-processing tasks.

Lesson 2 • Conditional Statements

Teaches if, elif, and else blocks with truthiness evaluation. Enables students to branch program behavior based on runtime data.

Lesson 3 • Exception Handling Basics

Teaches try, except, finally, and raising exceptions. Connects control flow to robust error management in real programs.

Lesson 4 • Comprehensions and Generators

Introduces list, dict, and set comprehensions plus generator expressions. Students write concise, Pythonic iteration patterns.

Lesson 1 • Recursion and Memoization

Covers recursive function design, base cases, and caching with functools. Students solve hierarchical problems efficiently.

Lesson 2 • Lambda Functions and Higher-Order Functions

Introduces anonymous functions and built-ins like map, filter, and sorted. Connects functional patterns to concise data transformation.

Lesson 3 • Defining and Calling Functions

Covers def syntax, return values, and calling conventions. Establishes the building block for all modular code in later chapters.

Lesson 4 • Scope, Namespaces, and Closures

Explains LEGB scope rules, global/nonlocal keywords, and closures. Students avoid common scoping bugs in nested code.

Lesson 1 • Tuples and Immutable Sequences

Explains tuple creation, packing, unpacking, and use cases. Students choose tuples when immutability and performance matter.

Lesson 2 • Dictionaries: Keys, Values, and Methods

Covers dict creation, access patterns, and iteration methods. Students build key-value stores central to most Python applications.

Lesson 3 • Choosing and Nesting Data Structures

Analyzes time complexity trade-offs and nested structure patterns. Students design efficient composite data models for real problems.

Lesson 4 • Lists: Creation, Access, and Mutation

Covers list literals, indexing, slicing, and in-place methods. Provides the most-used collection foundation for all data tasks.

Lesson 1 • Encapsulation and Properties

Explains name mangling, @property, and getter/setter patterns. Students enforce data integrity through controlled attribute access.

Lesson 2 • Classes, Objects, and Attributes

Introduces class definition, __init__, and instance vs. class attributes. Establishes the object model all OOP patterns build upon.

Lesson 3 • Dunder Methods and Operator Overloading

Covers __str__, __repr__, __eq__, __lt__, and arithmetic dunders. Students make custom objects behave like built-in Python types.

Lesson 4 • Methods: Instance, Class, and Static

Covers the three method types and their decorators. Students choose the correct method type for each behavioral responsibility.

Lesson 1 • Virtual Environments and Package Management

Explains venv, pip, and requirements files for dependency isolation. Students maintain reproducible project environments across machines.

Lesson 2 • Essential Standard Library Modules

Surveys os, sys, pathlib, datetime, math, and random. Students solve common tasks without third-party dependencies.

Lesson 3 • Creating and Importing Modules

Covers import, from-import, aliasing, and __name__ guard. Students split code across files while controlling what each module exposes.

Lesson 4 • Building Python Packages

Teaches __init__.py, package structure, and namespace packages. Students organize large codebases into distributable, importable units.

Lesson 1 • XML and Configuration File Formats

Introduces xml.etree.ElementTree and configparser for INI files. Students handle legacy and configuration data formats in enterprise contexts.

Lesson 2 • JSON Parsing and Serialization

Covers json.loads, json.dumps, and file-based JSON I/O. Students exchange structured data with web services and config files.

Lesson 3 • Data Validation and Error Handling

Covers schema validation, type coercion, and defensive parsing patterns. Students build pipelines that handle malformed external data gracefully.

Lesson 4 • Working with CSV Files

Teaches csv.reader, csv.writer, and DictReader for tabular data. Connects file I/O skills to the most common data exchange format.

Lesson 1 • Testing with pytest

Introduces pytest fixtures, parametrize, and plugins for modern testing. Students write concise, powerful tests with minimal boilerplate.

Lesson 2 • Code Quality: Linting and Formatting

Teaches PEP 8 standards, flake8, black, and type hints with mypy. Students produce consistent, readable code that meets professional team standards.

Lesson 3 • Mocking and Test Isolation

Covers unittest.mock, MagicMock, and patch for isolating dependencies. Students test code that relies on external systems without live connections.

Lesson 4 • Debugging Techniques and Tools

Covers print debugging, pdb, and IDE breakpoints for tracing bugs. Students locate and fix defects faster using structured debugging workflows.