Complete Python Course Bootcamp | Python Libraries Unlocked

Install Visual Studio Code for Python programming, set up the Microsoft Python extension, open a project folder, and run Python files in Visual Studio Code across Windows, macOS, and Linux.

Master the Python if conditional statement by learning its three parts: the if keyword, a boolean expression, and the indented code block, and how true or false conditions control execution.

Master python if-else conditional statements by exploring syntax, boolean expressions, and flowcharts, then apply user input and print outcomes such as 'try again' or 'you have passed the exam'.

Implement an if-else program in Python that reads user input and classifies it as a digit or a string using the isdigit method. Practice input handling and conditional flow.

Explore how to implement an if-elif-else ladder in Python, including syntax, flow control, and handling user input to classify numbers as positive, negative, or zero.

build a python program to check divisibility by five or three, print the five message, the buzz message for three or both, and the number otherwise; includes a flowchart.

Explore structural pattern matching and switch statement in Python 3.10, using match and case to compare a subject against patterns and execute code, with a wildcard default for unmatched cases.

Explore Python's range function to generate integer sequences, learn start, stop (stop not included), and step parameters, and see how unpacking and loop usage control output.

Master the Python for loop to iterate over sequences using range, with for, in, and a loop body, and print results like hello world multiple times.

Learn to write a Python program that sums numbers from 1 to a user-specified number using a for loop and range, converting input and printing the resulting sum.

Demonstrate how a loop inside another loop forms a nested for loop in Python to iterate rows and columns, enabling multi-dimensional arrays and basic image processing tasks.

Create a 3x3 square pattern with nested for loops and range. Print stars on the same line using the end parameter, then insert a blank line after each row.

Explore how while loops in Python execute code while a boolean condition is true, including syntax, increments, the else clause, and how this differs from for loops.

Learn to build a pyramid star pattern with nested while loops, calculating stars and left blanks per row using a simple formula and printing approach.

Learn to count digits in a user-entered number using floor division by ten and a while loop, without built-in functions, by updating a counter and printing the digit count.

Explore the break keyword in Python by building a program with a loop that reads numbers until an alphabet breaks the loop, then computes the average using sum and total_length.

Explore collection data types in Python, including list, tuple, set, string, and dictionary, which store heterogeneous items in an ordered group using a single variable.

Explore lists in Python: define lists with square brackets, access items by zero-based indexing, check length with len, and support homogeneous and heterogeneous data types, demonstrating mutability.

Learn Python lists by concatenating lists, declaring empty lists, appending items, and removing elements, while examining indexing, length, and mutability.

Master slicing in Python to extract list portions using start, end, and optional step; leverage positive and negative indexing and colon syntax to include end items and reverse order.

Master loops and lists by iterating list items with a for loop, printing index and item in tabular form, and using enumerate to simplify indexing.

Count how many times each number appears in a list using nested loops and a checked list to avoid duplication, printing counts without list comprehension or filter.

Learn list comprehension in Python to create a new list from an existing sequence in one line, using a for loop and if condition, and apply it to square values.

Explore tuples in Python by declaring immutable sequences, accessing items with indexing and slicing, and handling single-item tuples with a trailing comma.

Explore Python set operations with unions, intersections, differences, and symmetric differences on A and B, and implement these concepts in code using built-in methods.

Explore dictionaries in Python, learn how they are mutable, store data as key-value pairs, access items by key with indexing or get, and merge, update, or delete entries.

Learn to unpack dictionary data using keys, values, and items, loop with enumerate to create an index‑key‑value table, and extract keys and values in one line.

Sort dictionaries in Python using the built-in sorted function, by keys or by values, with reverse and a key lambda, while converting dicts to lists with items.

Learn dictionary comprehension in Python by transforming a salary dictionary: apply a 25% bonus for salaries over 10,000, keeping others unchanged, using item unpacking.

Explore how strings behave in Python, including indexing, slicing, and negative indexing, and learn to reverse strings and count digits using a for loop and membership checks.

Learn how a function is a named, reusable block with a unique name, parameters, a mandatory body, an optional return, and distinguish it from a method inside a class.

Define a Python function with the def keyword, a name, empty parameters, and a colon, then call it to see its print output and built-in function behavior.

Explore how function parameters and arguments work in Python, using built-in functions to show a receiver, a signature, and returns. Learn to define parameters, pass values, and observe Python’s behavior.

Learn how the return keyword—the opposite of parameters—sends a function's result to the caller and ends execution, contrasting with print, with examples of sum, cube, square, and exponent.

Build a basic statistics program in python by importing the statistics module, aliasing as sd, and returning a four-value tuple of median, mean, standard deviation, and mode for a list.

Learn named tuple, a datatype imported from collections that acts like a dictionary yet is a tuple with named fields accessed by dot notation and index, median, mean, and mode.

Explore how doc strings document functions, write a docstring with six quotation marks, and use the help function to reveal parameters and returns like mean, median, and standard deviation.

Explore the four types of function arguments in Python—positional, default, keyword, and arbitrary—through practical examples and parameter order concepts.

In the complete Python course bootcamp, learn how to pass unlimited positional arguments in Python using *args, implement a sum function, and iterate over args to compute the total.

Explore the difference between args and kwargs, learn how to define functions with unlimited keyword arguments using **kwargs, inspect kwargs as a dictionary, iterate with items(), and print formatted results.

Explore global and local variables in Python, understand namespaces and scope, and learn how non local variables arise in nested functions, with practical examples.

Explore how Python stores objects in namespaces, including built-in, global, and local namespaces, and how these isolated pools carry unique identifiers and lifetimes.

Explore recursion by implementing a recursive function that calls itself, processes user input, and sums numbers, using a base case and short-circuiting to stop.

Explore recursion in Python by building a recursive function that prints numbers from 0 to 9, with a base case to stop at 9 and an optimized condition.

Practice recursion in Python by implementing a factorial calculator using a recursive function, including the base case and recursive calls that multiply up during unwinding.

Explore how iterators in Python convert iterable objects like lists, tuples, and dictionaries with iter(), then use next() to access elements one by one, setting up for generators.

Create a custom range function in Python using a generator, accepting start, stop, and step, iterating with a while loop and yielding values to use in for loops.

Explore how nested functions work, with an outer function containing an inner function. See how inner functions access outer variables and parameters, enabling encapsulation, helper functions, closures, and decorators.

discover how nested functions act as helpers to print a pattern for each message, with an outer function gathering messages and an inner function printing equal signs and the message.

Explore how a function returns a nested function, with an inner function that squares a number, and the outer function returning it. This builds closures and function factories for Python.

Explore how decorators add functionality to existing functions by wrapping a simple print with an extra message, and learn two decorator approaches, with and without the @ syntax.

Explore anonymous functions in Python by mastering lambda expressions, parameters, and expressions that yield function objects, and learn two ways to call them.

Learn how lambda functions serve as inner functions to create closures and factory functions in Python, demonstrated through computing exponents and returning function objects.

Learn to use lambda functions as decorators in Python, transforming a simple sum function into a sum of squares, then into a squared final result through nested lambdas.

Learn how to use the filter function in python to filter lists and dictionaries by a condition using regular and lambda functions, with examples for even and odd numbers.

Develop a python prime number filter by implementing a function that tests divisibility with a for loop, using a flag and flowchart logic to return true for primes.

Learn to clean a dictionary by filtering out none values and outliers using a lambda-based filter, converting items to a dictionary, and generating a final clean dataset.

Explore procedural versus object oriented programming, and learn how classes, objects, methods, and attributes form the foundation of OOP with the four pillars: inheritance, encapsulation, abstraction, and polymorphism.

Learn to write your first object oriented program in Python by defining a class as a blueprint, creating objects, and printing hello world while exploring memory addresses with id.

Explore object-oriented programming in Python by building a class with name input and age checker methods, using self, type casting to int, and creating and using objects.

Create a new input method inside a class to collect name and edge from the user using the self keyword, wiring them to self.name and self.edge.

Extend the class with max and min methods that compute values from a numbers list. Fix initialization by using a first item to avoid bias and introduce getters and setters.

Compare instance variables and class variables in Python, using a computer class example. Learn how self-based instance data differs from class-wide values, and how namespaces govern access.

Explore Python method types—instance, class, and static methods—using decorators, access patterns, and practical examples, plus the property decorator for getters.

Explore python inheritance by comparing an animal base class with a dog derived class, placing common attributes in the parent and specifics in the child.

Explore multiple inheritance and the method resolution order in Python, using class hierarchies and diamond inheritance to show bottom-to-top and left-to-right resolution with linearization.

Explore encapsulation in Python, differentiate public, protected, and private attributes, and implement getters and setters via the property decorator to protect data in a class.

Explore dunder methods and their role in operator overloading and polymorphism, implementing __init__, __str__, __repr__, __abs__, and __add__ to customize object behavior.

Master polymorphism in Python by inspecting operator overloading and method overriding. Learn about function overloading and duck typing.

Explore how duck typing in Python makes methods matter more than object identity, using dynamic language features and polymorphism to determine behavior.

Learn how Python handles syntax errors, logical errors, and exceptions with try-except-else-finally blocks. Explore common exceptions such as file not found, zero division, and import errors.

Learn how the raise keyword in Python creates and propagates exceptions, enforces input validation for negative numbers, and supports handling or re-raising errors with try and except.

Learn to write to a text file in python by opening with the with keyword, using write mode and utf-8 encoding; file is created if missing and you can read/write.

Learn to handle JSON in Python by importing the JSON module, converting between dictionaries and JSON strings, and reading from and writing to JSON files with load, dump, and indentation.

Install the Python interpreter from the official site, install PyCharm community edition as your development environment, and create a new project with a virtual environment to keep dependencies isolated.

Explore the Pillow library in Python to perform image operations, including per-pixel operations, masking, transparency, filters like blurring and smoothing, brightness/contrast/sharpening, adding text, and drawing shapes.

Discover basic image operations in Pillow by installing the Pillow library, importing PIL, opening and displaying an image, and printing its name, size, format, width, height, and RGB mode.

Resize images in pillow by passing a width and height as a tuple, then view the resized result. Use image.size to determine original dimensions and resize to half the original.

Learn to merge two images by creating a new white background canvas, pasting image one and image two at defined coordinates, and extending to three to five images.

Blend two same size images in Pillow using Image.blend with an alpha value between 0 and 1 to control the mix, producing outputs from image one only to image three.

Use Pillow to rotate images by specified degrees, such as 45 and 90, and display the rotated image.

Learn to blur images in Pillow using an image filter. Choose simple blur, box blur, or Gershman blur, display, and save as JPEG.

Explore Pillow image filters, including blur, contour, detail, edge enhancement, emboss, find edges, and smooth and sharpen options to transform images.

Group images in Pillow and crop using left, top, right, and bottom boundaries to adjust the visible area. Flip images with transpose, including horizontal, vertical, and 90-degree rotations.

Learn to draw basic shapes on images using Pillow, including lines, arcs and semicircles, and create ellipses, rectangles, and rounded rectangles with position, size, color, and fill options.

Learn how to convert colors from text to rgb values using image color utilities, including hex codes and color names, and display the results in code.

Learn how to write text on images using Pillow, including loading fonts, creating a drawing surface, setting text size and color, and positioning text on an image.

Discover how numpy provides fast numerical operations with array-based data in Python, covering single and multi-dimensional arrays, indexing and subscripts, and performance advantages over Python lists.

Install numpy via pip in the terminal, import numpy as np, create arrays from Python lists with np.array, print them, and access elements by 0-based indexing.

Explore dimensions and shapes in numpy arrays, from single to multi-dimensional forms. Learn how shape and dimension differ, read memory diagrams, and map axes in two- and three-dimensional arrays.

Explore practical work on dimensions and shapes in Python arrays, learning how to determine and print the dimension and shape of one-, two-, and three-dimensional data.

Explore numpy arange to create arrays with start, end, and step, learn reshaping to multi-dimensional arrays, and generate arrays of ones and zeros for versatile data handling.

Learn how numpy's flatten converts multi-dimensional arrays to a single dimension, using C order and F order (column-major), and how transpose swaps rows and columns.

Learn how numpy stacking works, including stick versus concatenation, how stacking merges arrays while keeping them separate, and the depth stack concept (destek) with practical examples.

Explore the addition function of the collector module and the center function of the character module in NumPy, with hands-on examples that merge lists by position and center strings.

Explore how the capitalized, title, lower, and upper functions format strings in Python, with practical examples like hello and Python.

Master splitting strings with the split function and split lines to create separate elements from text, using separators and newline characters for practical data handling in Python.

Master stripping in numpy by removing whitespace or chosen characters from strings, using strip on single and nested arrays with step-by-step looping examples.

Explore how the join function combines array elements with a separator and how the replace function substitutes selected words within strings, using practical Python examples.

Explore NumPy arithmetic on a 3x3 array and a 1d vector, performing addition, subtraction, multiplication, and division, and compare row-wise versus column-wise results.

Learn the basics of slicing in numpy, from single-dimensional arrays to multi-dimensional arrays, using start, end (end exclusive), and step parameters on zero-based indices to select rows and columns.

Learn how to iterate through multi-dimensional numpy arrays efficiently using a built-in iterating function, avoiding complex nested loops.

Explore numpy resize, which changes an array to a new shape without honoring the original element count, unlike reshape; elements may repeat to fill the new size.

Explore internal numpy operations by adding arrays element-wise, performing row-wise and column-wise sums, and understanding how numbers combine across two dimensions.