Complete Python Programming Course: Beginner to Advanced

Discover how Python variables store data in memory, reference values, and enable computations with integers, floats, strings, booleans, and none. Grasp dynamic typing and common name errors.

Discover how to swap two variables in Python, compare a wrong approach, use a temporary variable, and master the one-line tuple unpacking with x, y = y, x.

Explore how id() provides a unique identifier for every object in Python. See how literals share objects and how the is operator checks identity, revealing memory addresses.

Discover how Python's id() returns a unique identifier for each object, how literals may share the same object in memory, and how the is operator tests object identity.

Learn Python lists as containers for multiple items, including creation, indexing (positive and negative), and core operations like append, insert, remove, pop, del, plus max, min, sum, reverse, and sort.

Discover how tuples in Python provide fast, immutable collections that are ordered and indexable. They support mixed types, indexing and slicing, and offer performance advantages over lists.

Learn Python sets: a distinct, unordered collection stored with hashing that supports fast union, intersection, difference, and symmetric difference, with guidance on creating empty sets using set().

Learn how dictionaries store key-value pairs in Python, with distinct keys and unordered order. Use indexing, get, in, len, pop, del, and popitem to access, update, and remove items.

Master type conversion in Python by contrasting implicit and explicit conversions, convert between int, float, bool, and string, and view binary, octal, and hexadecimal representations with bin, oct, and hex.

Discover how the print function in Python outputs values to the screen, how to pass multiple arguments, and how end, sep, and default new line shape the output.

Learn how Python's input() reads user input as a string, waits for enter, and can be converted to integers with int() for tasks like summing two numbers and printing results.

Explore arithmetic operators in Python, including addition, subtraction, multiplication, division, floor division, modulo, and power. Learn operator precedence, associativity, brackets, and type conversion to evaluate expressions correctly.

Explore Python's logical operators, including and, or, not, with short-circuiting, boolean expressions, and non-boolean results from strings and lists.

Explore identity comparison operators in python, using is and is not to compare object IDs and memory locations; see how literals may share references, while containers like lists do not.

Explore how the in and not in operators test membership in Python strings, dictionaries, and lists, returning booleans for substrings, keys, or elements.

Explore bitwise operators in Python and how they operate on binary representations, with examples of and, or, and xor on numbers like 3 and 6, plus decimal–binary conversions using bin.

Explore Python bitwise operators, including left shift doubling by powers of two, right shift dividing by powers of two, and bitwise not toggling bits, with two's complement for negatives.

Learn to calculate the nth term of an arithmetic progression in Python using a + (n-1)d, illustrated by a salary puzzle where monthly pay rises by 2000 rupees.

Explore computing the nth term of a geometric progression in Python using a * r**(n-1), with inputs a, r, n, and a salary-doubling puzzle to illustrate.

Learn to compute the sum of the first n natural numbers using the formula n(n+1)/2, with 10 and 100 day examples and a Python implementation.

Learn to extract the last digit of a user-provided number in Python using modulo 10, with a robust approach for negative values via absolute value.

Learn to compute the day before by subtracting n days from d using modulo 7 in Python, with 0 as Sunday and 6 as Saturday, handling large n.

Learn to use if, else, and elif in Python to execute code conditionally, handle input validation, and categorize numbers as positive/negative/zero with even/odd checks, using proper indentation and colons.

Understand how parity determines the winner in a one-coin-per-turn game in Python, using an if-else program that outputs 'you' or 'opponent' based on the number of coins.

Demonstrate how to find the largest of three numbers in Python using if statements, compare a two-comparison approach to the six-comparisons method, and show the max function for multiple inputs.

Write a Python program that determines leap years by checking if a year is divisible by 4 but not by 100, unless it is divisible by 400.

Design a basic Python calculator that displays a menu for addition, subtraction, and multiplication, prompts for two numbers, validates choices, and exits on invalid input.

Explore loops in Python to print the table of a given number and the first m multiples, and traverse collections or run services in infinite loops.

Discover how the while loop in Python repeats statements using a condition and indentation, controlled by a counter i, with infinite loop examples and printing geeksforgeeks n times.

Learn Python's range function, which generates numbers. Range(n) yields 0 to n-1, range(a, b) yields a to b-1, and range(a, b, step) yields a to b-1 by step.

Learn how the Python for loop iterates over lists, strings, and ranges. See how to access items with a loop variable and compare to for loops in other languages.

print the table of a given number in python using while and for loops, taking n and m as inputs to display the first m multiples.

Explore how the break statement in Python stops a loop when it finds the smallest divisor greater than one, with for and while loop examples.

Explore how to use the continue statement in Python with a for loop to print numbers not multiples of 5, and see an alternate solution without continue.

Explains nested loops in Python using an outer loop 1 to 10 and inner loop for each table, showing nesting up to three levels and traversing a list of lists.

Learn to print an n by n star square in Python using nested loops and range(0, n); print stars separated by spaces on each row.

Print a triangle pattern in Python by looping with range and printing i+1 stars on each line, using an inner loop and the end parameter to stay on one line.

learn to print an inverted triangle of stars in Python using nested loops and the range function, taking an input n and printing n, n-1, ..., 1 stars per row.

Learn to print a Python pyramid pattern using nested loops; place spaces as n minus i minus one and stars as two times i plus one per row.

Learn to count the digits of a positive integer by repeatedly floor-dividing by ten in a loop until zero, then print the digit count with a Python program.

Learn how to compute n factorial in python by looping from 2 to n and multiplying results, or by using math.factorial, with connections to arrangements and zero factorial.

Explore the greatest common divisor in Python by building a simple gcd program, testing divisibility up to the smaller number, and comparing the Euclidean algorithm and math.gcd.

Learn to compute the least common multiple in Python by a brute-force search from max(a, b) to a*b and by using math.gcd for a library approach.

Examine the Fibonacci sequence through a stair-climbing problem, showing how each term equals the sum of the two previous terms and implementing a Python solution.

Learn how to check if a number is prime in Python by testing divisibility from 2 to n-1 with a for loop, modulo, and a break-else pattern.

Learn how to find all divisors of a number and print them in Python, using for loops with range(1, n+1) and a while loop, based on whether x divides n.

Exploit the square-root optimization to list all divisors by printing paired factors and handling perfect squares, then apply the same approach to efficiently test primality.

Explore functions in Python, using def to define reusable blocks that print dates or greetings, accept parameters, and return values for flexible, centralized formatting.

Discover how functions reduce code redundancy, enable abstraction through library functions, enhance maintenance, and improve modularity by organizing input, processing, and output while avoiding variable name collisions.

Understand how python functions execute and return control via a call stack. See how main calls fun_one and fun_two and how local variables are managed on the stack.

Explore how default arguments let you omit values in Python functions, using default values and keyword arguments, and learn that after a default, all following arguments must be default.

Explore keyword arguments and their contrast with positional arguments by using id, name, and price in any order, improving readability and flexibility.

Explore variable length arguments in Python, using *args for positional inputs and **kwargs for key-value pairs, and learn to mix with fixed parameters and dictionaries.

Explore how Python passes parameters by object reference, showing that immutable types aren’t modified by assignment, while mutable lists reflect in the caller through in-place changes.

Learn how Python functions can return multiple values using tuples, lists, or dictionaries, and unpack them into separate variables for printing or further calculations.

Discover how global variables in Python are defined outside functions, how local variables shadow them inside functions, and how to modify globals with the global keyword and the globals() function.

Find the first digit of a positive number in Python using two methods: iterative division by 10, or log10 with powers to extract the digit.

learn to compute prime factorization by counting how many times a prime divides a number, printing each factor with a simple loop and is_prime check; examples include 100 and 15.

Explore strings in Python as sequences of characters and how ASCII and Unicode store text data. Recognize strings are immutable and use single, double, or triple quotes.

Explore escape sequences and raw strings in Python, and learn how backslashes, quotes, and newline characters affect string literals. Apply these concepts to avoid syntax errors and write robust code.

Discover how to format strings in Python using percent style, the format method, and f-strings. Apply variables, expressions, and function calls inside f-strings for readable, runtime-evaluated outputs.

Use the in operator to confirm substrings and not to negate, concatenate with the plus operator, locate positions with index or rindex, and raise a value error when absent.

Explore python string operations such as len, upper, lower, islower, isupper, starts with, ends with, split, join, strip, lstrip, rstrip, and find, including start and end parameters.

Learn how Python compares strings lexicographically by character, using Unicode codes and ASCII values; uncover how case affects order and how ord reveals code points.

Explore pattern searching in Python by finding all occurrences of a pattern within a text using string methods and the find function, with step-by-step printing of each index.

Learn to check palindromes in Python by comparing characters from the ends using a two-pointer approach, handling even and odd lengths, and outputting yes or no.

Reverse a string in Python by building the reverse and printing it, or with a one-line slice. Understand string immutability and slice syntax, such as s[::-1], to obtain the reverse.

Convert a non-negative integer to its binary string in Python, handling zero as a corner case. Use a naive division-by-two approach and a concise bin-based method with slicing.

Convert a binary string to its decimal value by traversing bits, multiplying each by the corresponding power of two, and summing the results. Use Python's int(binary_string, 2) for direct conversion.

Explore how Python slicing works for lists, tuples, and strings using start, stop, and step, including defaults and negative indices.

Write a Python function that takes a list and a value x and returns a new list containing only the elements smaller than x, preserving their original order.

Learn to separate a list into evens and odds by writing a function that traverses the list, checks divisibility by 2, appends evens and odds accordingly, and returns a tuple.

Explore Python comprehensions, including list, set, and dictionary, showing how to create lists from iterables with one-line syntax, filter evens and odds, and invert mappings with zip.

Compute the average or mean of a list by summing elements and dividing by the count, via a custom Python function or using sum and length, with real-world examples.

Learn to count distinct elements in a Python list, from a looping approach to using a set for efficient counting, including time-saving one-line solutions.

Check if a list is sorted in non-decreasing order by a linear traversal, treating empty or single-element lists as sorted, and print yes or no using the sorted function.

Demystifies object-oriented programming by organizing code into entities like student, faculty, and course, each with data and methods, so objects can interact.

Explore Python classes and objects, define a complex class with data members and methods, initialize with __init__, access via self and the dot operator, and build object‑oriented software.

Encapsulation hides internal data with private members and controlled access, letting you change representation without breaking code. Use setters for validation (marks, email) and getters to expose data for maintainability.

Learn how class attributes are shared by all objects and how instance attributes are unique to each object. The lecture covers accessing, adding, and shadowing, with Noida and NCR examples.

Explore Python member access rules, including default public access, single underscore for internal use, and double underscore name mangling, with practical examples.

Explore Python decorators that transform function behavior by treating functions as first-class objects and using inner functions; learn the @ syntax and how decorators enable static and class methods.

Learn how class methods modify class attributes and create instances using the cls parameter and decorators, and use static methods as general-purpose utilities not tied to any class.

Explore Python inheritance to promote code reuse, building a person base class with student and faculty subclasses, using super to initialize shared fields and extend with unique attributes.

Explore python inheritance types—single, multi-level, multiple, and hybrid—with real-world examples, including the diamond problem. Learn to override methods and call parent methods with super in subclass hierarchies.

Explore how Python handles multiple inheritance, including constructor calls through super, method resolution order, and why the diamond problem is avoided yet complexity encourages caution.

Explore polymorphism in Python, contrasting static and dynamic forms, showing how dynamic typing lets a single function handle multiple types and containers (lists, tuples, sets) without overloading.

Explore abstraction in object-oriented programming by defining abstract classes and declaring methods without implementations, establishing a contract that concrete shapes or employees must implement draw, get area, and other methods.

Demonstrate polymorphism through method overriding in derived classes, enabling a single loop to print details across different employee types, with shared method names and parameters.

Explore Python operator overloading using magic methods, as shown by a Product class that sums prices with the plus operator; covers __init__ and other overloadable methods and readability debates.

Explains how to create abstract classes in Python using the abc module, with abstractmethod decorators and concrete methods, and shows why you cannot instantiate abstract classes like Polygon.