Python.
Practical Python for automation, data engineering, machine learning, AI, DevOps, backend development, and testing.
Beginner
Start here — no prior experience needed
Python Variables and Type System
Understand variables, dynamic typing, scoping, and reference semantics in Python.
Python Functions and Parameters
Master defining functions, positional arguments, keyword arguments, and lambda functions.
Setting Up Python
Install Python, configure pip and virtual environments, set up VS Code, and run your first program the right way.
Python Data Types
Master Python's built-in data types: int, float, str, bool, None, and how to inspect and convert between them.
Building a Python CLI Tool
Learn how to build a CLI utility with argparse, structure your project, and package it.
Object-Oriented Programming in Python
Learn classes, instances, inheritance, dunder methods, and encapsulation with real-world examples.
Python Operators
Learn Python's arithmetic, comparison, logical, bitwise, and walrus operators with practical examples.
Control Flow in Python
Master if/elif/else, match-case, for and while loops, break/continue, and list comprehensions.
Python Data Structures
Master lists, tuples, dictionaries, sets, and comprehensions with practical production-ready examples.
Python Strings
String methods, f-strings, formatting, slicing, and regex basics — everything you need to work with text in Python.
Python Collections
Deep dive into list, dict, set, tuple, and the powerful collections module: deque, defaultdict, Counter, and namedtuple.
Python Modules and Packages
Learn how to import modules, create packages, manage pip dependencies, and structure Python projects with virtual environments.
Introduction to Python
Learn what Python is, its history, use cases, and why it's one of the most in-demand programming languages today.
Intermediate
For developers with core concepts down
Error Handling in Python
Handle exceptions gracefully with try/except/finally, create custom exceptions, and use logging and traceback effectively.
Python Decorators and Closures
Understand closures, write function and class decorators, and use functools for production-grade wrapping patterns.
File I/O, pathlib, and JSON in Python
Read and write files safely using context managers, navigate the filesystem with pathlib, and handle JSON and CSV data.
Python Concurrency
Master threading, multiprocessing, asyncio, and concurrent.futures to write efficient parallel Python programs.
Testing Python Code
Write reliable tests with pytest and unittest, use fixtures and parametrize, mock dependencies, and measure coverage.
Python Security
Write secure Python code: validate inputs, prevent SQL injection, handle secrets safely, and use hashlib and the secrets module.
Python Generators
Master yield, generator expressions, itertools, and infinite sequences to write memory-efficient Python code.
Python Context Managers
Master the with statement, contextlib utilities, and building custom context managers for clean resource handling.
Python Interview Prep
Top 30 Python interview questions with detailed answers and production-quality code examples for all levels.
Advanced
Production-grade patterns for experienced engineers
Python Memory Management
Understand Python's garbage collection, reference counting, weak references, __slots__, and memory profiling techniques.
Python Design Patterns
Implement classic design patterns in Python: singleton, factory, observer, strategy, and decorator with idiomatic Pythonic approaches.
Python Performance
Profile Python code with cProfile and timeit, vectorize with NumPy, cache with lru_cache, and identify real bottlenecks.
Async Python with asyncio
Master asynchronous programming in Python using asyncio, async/await, tasks, gather, and real HTTP concurrency with aiohttp.
Python Metaclasses
Understand Python's type system, metaclasses, __new__ and __init__, ABCMeta, and practical metaclass use cases.
Python Type Hints and Static Typing
Write self-documenting, safer Python code using type annotations, generics, Protocol, TypeVar, and runtime validation with Pydantic.