Complete Python Course

Lesson 1 • Input, Output, and String Formatting

Teaches print(), input(), and modern string formatting techniques. Enables interactive scripts and readable program output.

Lesson 2 • Variables and Built-in Data Types

Explains dynamic typing, variable assignment, and core types. Mastery here underpins every data-manipulation task ahead.

Lesson 3 • Core Syntax and Code Structure

Introduces indentation rules, comments, and statement structure. Correct syntax habits prevent errors throughout the course.

Lesson 4 • Operators and Expressions

Covers arithmetic, comparison, logical, and bitwise operators. Students combine operators to form meaningful computational expressions.

Lesson 1 • Exception Handling Basics

Covers try, except, else, and finally blocks for error management. Robust error handling prevents crashes in all subsequent projects.

Lesson 2 • Comprehensions and Generators

Introduces list, dict, and set comprehensions plus generator expressions. Produces concise, memory-efficient iteration patterns.

Lesson 3 • Conditional Statements

Covers if, elif, and else blocks with nested conditions. Builds decision-making logic essential for all real-world programs.

Lesson 4 • While Loops and Loop Control

Teaches while loops, break, continue, and else clauses. Students control loop termination precisely in complex scenarios.

Lesson 1 • Defining and Calling Functions

Covers def syntax, return values, and calling conventions. Functions are the primary unit of reuse in every Python project.

Lesson 2 • Advanced Parameter Techniques

Teaches default values, *args, **kwargs, and keyword-only params. Enables flexible APIs used in libraries and frameworks.

Lesson 3 • Scope, Closures, and Namespaces

Explains LEGB scope rules, global/nonlocal, and closure mechanics. Prevents subtle bugs caused by unintended variable sharing.

Lesson 4 • Lambda Functions and Functional Tools

Covers lambda expressions and built-ins map(), filter(), and functools. Enables concise functional-style data transformations.

Lesson 1 • Lists and Tuples

Covers list mutation, slicing, sorting, and immutable tuples. These sequences underpin data pipelines built in later chapters.

Lesson 2 • Collections Module

Introduces Counter, defaultdict, deque, and OrderedDict. Specialized containers solve common problems with less code.

Lesson 3 • Algorithmic Complexity and Selection

Explains Big-O notation for built-in operations and guides structure selection. Choosing correctly prevents performance bottlenecks at scale.

Lesson 4 • Strings as Sequences

Explores string methods, slicing, and encoding. String mastery is required for file parsing and API work covered later.

Lesson 1 • Methods and Properties

Teaches instance, class, and static methods plus @property. Controlled attribute access enforces data integrity across the codebase.

Lesson 2 • Classes, Objects, and Attributes

Covers class definition, __init__, instance vs. class attributes. Objects encapsulate state and behavior for modular design.

Lesson 3 • Inheritance and Polymorphism

Explains single and multiple inheritance, super(), and method overriding. Polymorphism enables flexible, interchangeable component design.

Lesson 4 • Dataclasses and Modern OOP Patterns

Introduces @dataclass, slots, and frozen instances for boilerplate reduction. Modern patterns produce safer, more readable class definitions.

Lesson 1 • Virtual Environments and Dependency Management

Explains venv, pip, and requirements files for isolated environments. Isolation prevents version conflicts in multi-project workflows.

Lesson 2 • Standard Library Essentials

Surveys os, sys, pathlib, datetime, json, and re modules. These built-ins solve common tasks without third-party dependencies.

Lesson 3 • Creating and Distributing Packages

Teaches __init__.py, subpackages, and pyproject.toml configuration. Proper packaging enables reuse across projects and teams.

Lesson 4 • Modules and Import System

Covers import, from-import, aliasing, and module search paths. Understanding imports prevents circular dependency and namespace conflicts.

Lesson 1 • HTTP APIs with requests and httpx

Covers GET, POST, headers, authentication, and error handling. API integration is a core skill for modern backend and data work.

Lesson 2 • File Reading and Writing

Covers open(), context managers, text vs. binary modes, and CSV. File I/O is the entry point for all data ingestion pipelines.

Lesson 3 • Working with Paths and the Filesystem

Teaches pathlib operations, directory traversal, and file metadata. Robust path handling prevents cross-platform compatibility issues.

Lesson 4 • Building REST APIs with FastAPI

Teaches route definition, request models, validation, and responses. Students expose their own data services via a production-ready framework.

Lesson 1 • Unit Testing with pytest

Covers test functions, assertions, fixtures, and parametrize. Automated tests catch regressions before code reaches production.

Lesson 2 • Profiling and Performance Optimization

Introduces cProfile, timeit, and memory_profiler for bottleneck detection. Data-driven optimization avoids premature and misguided tuning.

Lesson 3 • Code Quality and Static Analysis

Covers type hints, mypy, flake8, and black for maintainable codebases. Enforced standards reduce bugs and ease team code reviews.

Lesson 4 • Debugging Techniques and Tools

Covers pdb, IDE debuggers, breakpoints, and logging-based debugging. Systematic debugging reduces time spent diagnosing production issues.