Python Mastery: From Absolute Beginner to Advanced OOP

Verify python installation on Windows, macOS, and Linux; compare python version commands; install via python.org, homebrew, apt, or from source; then explore the interactive interpreter.

Choose from PyCharm, Visual Studio Code, or Jupyter Notebook to boost Python work with debugging, project management, and code suggestions, while this course uses Visual Studio Code.

Explore Python syntax and the PEP 8 style guidelines, including indentation rules, four-space blocks, tab and space pitfalls, and snakecase naming for readable Python 3 code.

Explore Python's numeric types: int, float, and complex, and how they represent whole, decimal, and complex numbers. Learn about type coercion, string-to-integer conversion, float precision, and decimal module for arithmetic.

Explore how atomic objects copy values while reference objects share memory, and compare mutable versus immutable types across integers, strings, lists, and tuples with id demonstrations.

Explore the string data type in Python, including index access, slicing, immutability, methods (lower, upper, strip, replace, find, split, join, startswith, endswith, len), and formatting with percent, format, and f-strings.

Explore Python's list data type, a mutable, ordered collection that holds duplicates and elements of any type, with indexing, slicing, and operations like append, insert, del, and sort.

Master Python tuples: immutable, ordered collections that store multiple data types. Learn indexing, slicing, concatenation, repetition, membership tests, and unpacking, including packing and single element nuances.

Learn boolean data types in Python, using booleans true and false, comparison operators, and boolean operators such as and, or, not, plus the precedence rules for evaluating complex expressions.

master python dictionaries by creating, updating, and deleting key-value pairs; access values with keys or get, and use keys, values, update, pop, pop item, clear, and sorted for insertion order.

Explore how sets and frozensets in Python manage unique elements, support union, intersection, difference, and membership tests, and compare mutability and performance between sets and frozensets.

Explore Python's binary sequence types, bytes and bytearray, detailing creation, utf eight encoding, ascii basics, immutability versus mutability, slicing, decoding, and common byte operations.

Master Python control flow with if statements, else and pass, and the ternary operator for single-line decisions, then loop over lists, strings, and other iterables with for and while loops.

Explore nested data structures with lists and dictionaries, including a 3x3 grid and a users dictionary. Learn to access, iterate, and print structured data using nested loops and unpacking.

Explore list comprehensions in Python that replace for loops with concise expressions and optional filters. See range-based and nested loops with optional if-else logic.

Learn how the Python input() function captures user data as strings, uses prompts, and converts to int, float, and bool, with examples of concatenation, print, and lower-based yes/no handling.

Master defining and calling functions in Python with def and parentheses, maintain indentation, pass arguments, return values, and compose functions such as capitalized name and greet user.

Learn how positional and keyword arguments pass data to Python functions in their defined order and by name, including default values and examples like calculating shipping costs.

Learn to pack and unpack arguments in Python functions, using *args and **kwargs to accept variable positional and keyword inputs and unpack lists, tuples, and dictionaries into function calls.

Discover how Python lambda functions create small anonymous one-expression functions and become powerful when used with map and filter for concise, readable data transformations.

Explore Python variable scope, including local, enclosing, global, and built-in scopes, how names resolve via the LEGB rule, and how global and local variables interact and shadow.

Learn to handle errors in Python functions with try-except blocks, using specific and multiple exceptions, and optionally else and finally clauses to provide user-friendly messages and robust code.

Discover Python modules and import patterns by building a three-module project—gaming stats, player utils, and main—using from, import, and as aliases to calculate score, get rank, and format player stats.

Explore python decorators that wrap a function with a wrapper to extend behavior, use decorator syntax, and measure execution time with a timer example using time.sleep and built-in decorators.

Learn to generate a QR code in Python using the QR code library, with a reusable function that encodes a URL, and customize size, border, and colors.

Learn how Python treats every data piece as an object, uses classes as blueprints to create instances, distinguishes class and instance attributes, and accesses methods with dot notation.

Explore how Python defines instance, class, and static methods, showing how instance methods access attributes via self, class methods use cls, and static methods serve as utilities.

Explore Python's inheritance from the root object, contrast old and new style classes, and master single and multiple inheritance with dog, animal, and pet examples and the MRO.

Explore multi-level inheritance and hierarchical inheritance in Python, using animal, mammal, dog, and cat to illustrate base and derived classes, method resolution order, and shared methods.

Master composition in Python object-oriented programming by learning how a class contains other class instances, delegates tasks, and builds flexible, maintainable systems without inheritance, illustrated with a car and engine.

Explore polymorphism in Python by using inheritance and method overriding to let different objects share a common interface, with dynamic typing determining the actual behavior at runtime.

Explore encapsulation in Python by using classes to combine data and methods, control access with public, protected, and private members, and understand name mangling and access from outside the class.

Explore encapsulation in Python with getters, setters, and the property decorator to control access to private attributes like name and salary, add validation, and enable cleaner syntax.

Explore aggregation in python by modeling a library that holds book objects without owning them; books exist independently even if the library is destroyed, contrasting with composition.

Demonstrate abstraction in Python by hiding implementation details and exposing essential features, using abstract classes and abstract methods to enforce a common interface and enable polymorphism in subclasses.