Complete Python Course: From Zero to Professional

Installing Python, the REPL, print statements, comments, and why indentation matters.

The five core data types (int, float, str, bool, None), dynamic typing, type casting, memory references, and reading standard input.

String indexing and slicing, powerful string methods, and modern formatted strings.

Arithmetic, comparison, logical, and assignment operators — plus expression evaluation order.

Evaluating truth tables, if/elif/else routing, for and while loops, break, and continue.

Master break, continue, pass, loop else clauses, and nested loops with trace tables.

Build lists, dicts, and sets in one elegant line with comprehensions and generator expressions.

Mutable lists, immutable tuples, slicing, sorting, and common list methods.

Unordered sets for lightning-fast membership, and key-value dictionaries for real-world data.

Supercharge your data with Counter, defaultdict, deque, and namedtuple from the collections module.

Build nested dicts and lists, understand how references behave, and copy safely.

Define functions, parameters, default arguments, return values, and docstrings.

Anonymous one-line functions and flexible functions that accept any number of arguments.

LEGB scoping rules, closures that remember, and decorators that wrap functions with extra behavior.

Organize code into files, import between them, use the __name__ guard, and install packages with pip.

Object structure, __init__ constructor, instance parameters, methods, and parent-child overrides.

Deep-dive into inheritance, method overriding, polymorphism, isinstance, and the MRO.

Private attributes, @property for smart access, and dunder methods that customize objects.

Write less boilerplate with @dataclass, frozen data, and professional OOP best practices.

Read and write files safely with the with statement, work with paths, and handle CSV data.

try/except/else/finally, raising your own errors, and writing code that never crashes the user.

Lazy iteration with yield, memory-efficient pipelines, and the itertools toolbox.

Serialize Python objects to JSON, load API data, and build real-world data workflows.

assert, pytest, the debugger, and logging — write code that proves itself.

Bring everything together: functions, dicts, files, JSON, and a menu loop in one complete project.