Extensive Python Fundamentals in 4 Weeks

Master Python identifiers by learning valid naming rules, case sensitivity, and why keywords cannot be used as identifiers, with practical examples.

Explore Python keywords, including true, false, none, and, or, not, as, peg parser, and assert, with examples of boolean logic and value semantics.

Explore python keywords including async and await for concurrent code with the async IO library, and cover control flow, break, continue, class, def, and delete operations.

Discover how Python keywords like finally, try, except, for, import, from, global, in, is, lambda, non-local, pass, return, while, with, and yield guide resource cleanup, control flow, and module usage.

Explore Python statements, multi-line statements with backslashes or parentheses, and indentation rules for code blocks; master comments, docstrings, and the F function to access documentation.

Learn how Python variables and constants store data using named identifiers, with mnemonic naming, and understand assignment and type inference.

Assign and print variables to see the values, then define constants in a module, import them, and apply Python naming rules with uppercase letters and underscores.

Explains how Python operators work, covering arithmetic, comparison, logical, bitwise, and assignment operators, plus identity and membership checks, with examples like addition, modulus, and exponentiation.

Explore Python literals, including numeric, string, boolean, and special literals, and learn type conversions and collection types like lists, tuples, dictionaries, and sets.

Explore Python data types, including int, float, complex, list, string, tuple, set, dict, and boolean, and learn to declare, operate on, and inspect them with type and isinstance.

Master Python lists as mutable, heterogeneous sequences; learn zero-based indexing, slicing, and operations to replace, add, or delete elements.

Explore Python data types with a focus on tuples, their immutability, and how to index and slice them. Learn string basics, quoting rules, concatenation, and multi-line strings.

Explore Python data types by examining sets and dictionaries, focusing on sets' uniqueness and mutability and dictionaries as key-value maps; review booleans and preview type conversion.

Explains implicit vs explicit type conversion in Python with int, float, and string examples. Demonstrates type casting using int, float, and str, and highlights errors when combining incompatible types.

Explore Python data types (int, float, complex), type conversion (implicit and explicit), and core structures (lists, tuples, dictionaries, sets), plus strings and number representations in binary, octal, and hex.

Explore how floating point numbers behave in Python, why binary representation affects precision, and how the decimal module and the fractions module enable exact decimal calculations and rational arithmetic.

Explore python mathematics and random data handling by importing math and random, using cosine, exponential, logarithm, sinh, and random choices, plus a primer on unicode strings and encoding.

Learn to create strings in Python with single, double, and triple quotes, including multi-line strings and doc string, and how to print strings and variables while avoiding mixed quotes.

Explore how to access and slice Python strings using forward and backward indexing, negative indices, and the slicing operator, then validate length with len and handle index errors.

Explore how to access and slice strings in Python, then break them apart with partition, split, and join. Learn about string immutability and how to reassign values.

Master Python string operations, including concatenation and replication, membership and relational operators, and percent-formatting, with examples of iterating strings and applying these operators.

Explore Python's built-in functions such as enumerate and len, and master string handling with escape sequences, raw strings, and the string format method, including old-style formatting.

Master Python string methods, including format, upper, lower, title, capitalize, strip, and swapcase, with hands-on examples and troubleshooting tips.

Explore Python lists, a mutable, versatile sequence, and master creating lists, inserting and removing elements, indexing, slicing, and accessing nested lists.

Explore Python list operations, including mutability, adding, changing, and inserting elements; learn append, extend, insert, list concatenation, and repeating lists with multiplication.

Delete list items using del, and remove or pop elements with dedicated methods, then clear or slice to delete portions, including deleting the entire list.

Master built-in list functions in Python, including all, any, sorted, min, max, and len, with examples of list methods like append, extend, insert, remove, pop, and clear.

Master Python list comprehension to create new lists from existing sequences, compare it with for loops, and apply conditions, loops, and simple operations for efficient data processing.

Learn how Python tuples differ from lists: immutability, parentheses vs packing, creating and nesting tuples, indexing and slicing, negative indexing, and unpacking techniques for structured data.

Explore how tuples behave in Python data structures: immutable top-level elements, mutability within nested items, and operations like reassignment, concatenation, repetition, and deleting tuples with del.

Explore built-in functions and tuple methods such as len, max, min, sorted, and conversion to tuple, plus count, index, membership tests, and practical iteration examples.

Explore Python dictionaries as an unordered key-value store with unique, immutable keys and mutable values, accessed via square brackets or the get method.

Learn how to change or add dictionary elements using assignment, noting that keys are immutable while values are mutable, and use pop, clear, and del to remove items.

Explore built-in Python dictionary methods and functions, with examples on adding, removing, and deleting elements. Learn dictionary comprehension and related operations, including booleans and string representations.

Explore dictionary comprehension in Python by building dictionaries from expressions like square numbers, using optional for and if filters, and practice membership tests and iteration.

Discover Python sets as unordered collections of unique elements, create and modify them with add and update, remove items with discard or remove, and perform union or intersection.

Explore Python sets and perform union, intersection, difference, and symmetric difference using operators or set methods, with practical A and B examples.

Explore built-in set functions such as enumerate, len, max, min, sorted, and sum, and apply set operations like union, intersection, difference, and symmetric difference, including frozen sets and membership tests.

Learn how the print function outputs data to the screen or a file, format output with string format and the old printf style, and preview the upcoming input function topic.

Use Python's input function to read user data with prompts, convert input from string to int, float, or complex, and handle examples like names and arithmetic with two numbers.

Learn to collect multiple inputs in one line with Python input and split, assign to name, age, and phone number, print the details, and practice multiline input with a loop.

Explore Python input and output formatting by position and by name, using .format specifiers to align text with width, format numbers (integers, octal, binary, floats), and demonstrate string justification.

Learn to organize Python code into modules and import definitions into your program. Use from import aliases and dot notation to access module functions and understand module paths.

Define how Python uses namespaces to map names to objects, exposing built-in, global, enclosing, and local scopes, and show how the id function reveals object memory addresses.

Understand Python namespace and scope, including local, module global namespaces, and builtin namespaces, and how Python resolves names across nested scopes via local, global, builtin lookups and nonlocal usage.

Learn Python datetime fundamentals, from importing and creating date, time, and datetime objects to formatting with strftime and parsing with strptime, including time zones and UTC considerations.

Learn how to work with Python datetime part 2 by converting between timestamps and dates, applying time delta arithmetic, and handling time zones with dateutil tz and pytz.

Explore Python control flow, including conditional statements like if/else/elif, and for and while loops, with break, continue, and pass, all defined by indentation.

Master the python if statement to evaluate conditions and execute the true block using indentation, with examples of comparisons, printing results, and one-line shorthand.

Explore how the if else statement handles false cases and runs alternate code blocks. See indentation, examples with grid and numbers, and the one-line if else shortcut.

Learn to use Python if-elif-else control flow to chain multiple conditions, evaluate boolean expressions, and apply indentation and else blocks.

Learn how Python nested if statements enable a series of decisions, explore their syntax and indentation, and review practical examples using x and y for true and false conditions.

Learn to use for loops and while loops in Python to iterate over sequences, perform definite iteration, manage indentation, and apply the range function in subsequent lessons.

Master Python's range function with for loops, including start, stop, and step, and apply examples like summing numbers and printing sequences.

Explore Python control flow with for loops and range, combining if else blocks, and the for-else pattern, with examples classifying even and odd numbers and break behavior.

Explore Python control flow in for loops, mastering break, continue, and pass to exit, skip, or no-op within loops, with practical nested-loop examples.

Explore backward iteration in Python for loops, using reversed and range with a minus one step to reverse lists, and explore helpers like enumerate, zip, and sorted.

Explore nested for loops in Python, showing how an inner loop restarts for each outer loop and how to build multiplication tables and simple pyramids with range.

Learn three ways to access indices in for loops—enumerate, range, and the membership operator—and apply them to lists, strings, and splitting sentences.

Learn how to iterate lists with a for loop, access indices, and use range and list comprehension. Explore lists vs tuples, printing, and computing averages from numbers.

The lecture demonstrates using for loops to iterate over tuples, contrasts list and tuple mutability (lists are mutable, tuples immutable), and previews iterating over dictionaries with for loops.

Learn to iterate over Python dictionaries with for loops, accessing keys, values, and key-value pairs using iteration and dictionary methods such as values() and items() in practical examples.

Learn how to loop over a set with a for loop, exploring its unordered, unique elements and how to add or remove items, illustrated with a fruits example.

Explore how the Python while loop executes a block of code while a condition stays true, enabling indefinite iterations and automation. Learn its syntax and when to use it.

Explore Python control flow with while loops and for loops, including counter management, user input, summation, Fibonacci series, and nested loop examples.

Explore using a while loop inside a for loop and while with if else, including printing even and odd numbers up to the number entered and squaring odd numbers.

Learn how the while loop in Python uses an optional else block, and how break, continue, and pass control flow. See examples that print numbers and illustrate else behavior.

Master the continue in a while loop to skip iterations and print odd numbers below a user-provided limit; examine the pass statement and reverse looping, with preview of nested loops.

Master nested while loops with outer and inner iterations, learn while loop syntax and pyramid printing, and integrate for loops inside while; practice primes between 17 and 73.

Explore using while loops to iterate strings, lists, and numbers with practical examples, including indexing and incrementing, and preview break, continue, and pass control statements.

Learn how Python control statements break, continue, and pass manage loop execution by terminating, skipping, or doing nothing, with practical examples in for and while loops.

Explore Python control flow with break in nested loops and how continue and pass fit into examples like printing tables and letters in hello world.

Explore the Python continue statement as a jump that skips loop iterations in for and while loops, with examples like skipping spaces and using continue in nested loops.

Explore Python control flow statements, including break, continue, and pass, and see how they terminate loops, skip iterations, or perform no-ops within for and while loops.

Explore Python function basics, including defining functions, mandatory and optional arguments, recursion, anonymous lambdas, and function scope, then dive into modules, math and random functions, packages, and docstrings.

Define Python functions as self-contained blocks of code that may take parameters and return values, following dry principles. Distinguish built-in from user-defined functions and review syntax.

Learn how to define and call Python functions with and without parameters, create simple examples like greeting and display full name, and explore parameter types and docstrings.

Explore Python functions with single and multiple parameters, arguments versus parameters, and return values, including examples like area of a circle using pi.

Define Python functions with parameters using def and return statements to output the function's value; learn that return ends execution and that None is returned when no value is provided.

Learn to return multiple values from Python functions using the return statement and comma separation, with examples of addition, subtraction, multiplication, division, and returning booleans or lists.

Explore Python global, local, and non-local variables, understand variable scope across functions, and learn how global access differs from local life cycles and handling unbound local errors.

Explore local variables and scope in Python, identify name errors from accessing locals globally, compare global, local, and non-local variables, and learn non-local usage in nested functions.

Master how the Python global keyword lets you modify a global variable from inside a function, with scope rules and practical examples including nested contexts.

Learn how Python distinguishes parameters and arguments, and how to define functions with positional arguments and default values. Explore keyword arguments and variable-length (arbitrary) arguments with practical examples.

Explore Python function arguments and parameters, including default values, keyword and positional arguments, arbitrary length args, and passing functions as parameters, with practical examples.

Explore how a Python function calls itself to solve problems, with a factorial example, base condition, and notes on recursion depth and errors.

Learn about Python lambda functions, anonymous single-expression helpers, with syntax and usage examples; see how they take arguments, return one value, and stay scoped to their parameters and global namespace.

Explore how Python lambda functions serve as nameless helpers with filter, map, and reduce, including examples that filter even numbers and positive numbers, map doubles, and reduce sums.

Learn to create and import custom Python modules, reuse code across projects, and use built-in modules with import, from import, and alias for modular, maintainable code.

This lecture introduces the Python random module, shows how to import, seed the generator, and generate pseudo random numbers with random.random, noting determinism and encryption caveats.

Explore the Python math module, import math, and use functions like sqrt to perform accurate math operations; learn its limitation with complex numbers and preview future topics on Python packages.

Learn how to organize Python code into packages and modules. Use __init__.py for package initialization and import from packages with dot notation, including third party and user defined modules.

Discover the advantages and practices of user defined functions in Python, including defining, calling, and naming them. See an example that adds two numbers with input, float conversion, and return.

Learn Python docstrings: write single-line and multi-line docstrings for functions, classes, and modules; access via __doc__ or help(); generate docs with Sphinx and formats like Google and NumPy.

Explore object oriented programming in Python by combining data and methods inside classes and using objects to store attributes. Discover inheritance, encapsulation, polymorphism, method overloading, and decorators through practical examples.

Treat a class as a blueprint for creating objects with class and instance attributes. Illustrate with an employee management example, showing init, object instantiation, and dot-operator access.

Explore instance variables in Python classes, contrast with class variables, and learn to define and access per-object data using self, __init__, and the dot operator.

Dive into Python object oriented programming by distinguishing methods from functions and exploring instance, class, and static methods, constructors, decorators, and factory patterns for object creation.

Learn how class methods access and modify class variables across all instances, using an employee example; explore static methods and the decorator for isolated utility tasks.

Explore objects and classes in Python, creating objects, and using constructors: default, non-parameterized, and parameterized, to initialize attributes and manage memory.

Master python inheritance types: single, multiple, multi-level, hierarchical, and hybrid, through parent and child classes, the super function, is-subclass checks, and vehicle examples.

Learn how inheritance works, including super, subclass checks, and method overriding to extend parent behavior. Explore method resolution order in Python for single and multiple inheritance.

Explore encapsulation in Python, bundling data and methods into a class with public, protected, and private modifiers. Understand name mangling and private attributes, with public methods offering controlled access.

Demonstrates encapsulation in Python by using public, protected, and private access modifiers, and implements getters and setters to control access and validate data with an example employee class.

Explore the four essential object oriented programming concepts: inheritance, encapsulation, polymorphism, and abstraction. Apply them in Python with examples of getters and setters, name mangling, method overriding, and operator overloading.

Explore Python polymorphism by overriding built-in and magic methods, implementing polymorphism across classes and functions, and understanding method overloading limitations and workarounds.

Explore polymorphism through operator overloading in Python, using magic methods to redefine operators for numbers, strings, lists, and custom objects. Overload addition for salaries.

Explore abstraction in Python oop by hiding internal implementation and using hierarchical abstraction to manage complexity, with abstract classes and abstract methods defined via the ABC module.

Learn how Python decorators extend function behavior without altering the original code, by creating decorators that take and return functions, with examples of list and power decorators, arguments, and defaults.

Learn Python file handling: open and modes, read/write/append text and binary; navigate directories, get file attributes, pattern-match with glob, copy/move/rename/delete, and work with zip, csv, json and binary persistence.

Learn to list a folder with the os module, and search for files using startswith, endswith, fnmatch, glob, and pathlib glob pattern matching to filter results.

Explore file handling in Python part 3, including getting file attributes, scanning and traversing directories, copying, moving, renaming, and deleting files with os and shutil, plus timestamps.

Learn to create zip files, add files to existing archives, read contents, and extract files from zip archives using Python's zipfile module.

Learn to read and write text files, including line by line reading and append operations. Master csv and json handling, and persist Python objects to binary files.

Learn to read json files and pretty print with json dumps, and persist Python objects to binary files using pickle with serialize and deserialize steps.

Define Python exceptions and distinguish them from syntax errors, then explain why errors occur, how to identify them, and how to catch and resolve common builtin errors.

Learn to handle Python errors with try and except, catching specific exceptions such as NameError, TypeError, and AttributeError, and provide meaningful messages with multiple except blocks to keep programs running.

Master try and except with else and finally, illustrated by zero division and value errors. Learn to raise your own exceptions and craft error messages.

Apply comprehensive Python fundamentals by implementing three real-life projects: bank management system, car rental management system, and student management system, combining variables, data types, OOP, file handling, and CRUD.

Learn to build a bank management system in Python by defining a BankAccount class with account creation, display, modification, and balance operations. Implement deposits, withdrawals, and statements.

Develop and test a bank management system in Python fundamentals by building functions for creating accounts, writing to encrypted pickle files, and displaying, depositing, and withdrawing from accounts.

Master extensive python fundamentals by building a bank management system that creates, deletes, modifies, and displays accounts using pickle-based binary files, pathlib paths, and os file operations.

Learn to implement and test a bank management system in Python, handling errors and debugging. Create accounts, deposit funds, withdraw, check balance, display all records, and modify or close accounts.

Explore building a car rental management system in Python using object oriented programming, with classes, static methods, and a real time project focused on owner and user workflows.

implement a car rental management module by adding a weekly rental function, return flow, and a customer class to track rental time, basis, and billing calculations.

Build a Python car rental management system with a main driver and car class, featuring a menu-driven flow for owners and users, including total rent generated.

Part 5 of project implementation presents a menu-driven car rental management system in Python, featuring input validation, exception handling, and hourly or daily rental flows.

Create a command-line student information system that supports create, read, update, and delete operations, and stores data in raw and student databases, with color and pretty table displays.

Develop a car rental management system by implementing request car input, positive input checks, and return car logic, while demonstrating object oriented programming with classes and polymorphism in Python.