Algorithms + Data Structures + Coding Interviews with Python

Explains comb sort, a bubble-sort variant using a shrinking gap and a swap flag, with a Python implementation that reduces the gap by 1.3 until one.

Demonstrate selection sort with a Python implementation. Learn to find the minimum in the unsorted portion and swap it into place using outer and inner loops.

Explore radix sort, which uses counting sort as a subroutine to sort numbers by each digit (ones, tens, hundreds) in a stable pass.

Learn how binary search quickly finds a target in a sorted list by halving the search range using left, right, and mid indices, with both iterative and recursive Python implementations.

Demonstrates reversing a simple linked list in python using both iterative and recursive approaches, updating node links and head, and validating with a sample zero, one, two, three list.

Sorts a doubly linked list by swapping node data through a while-loop pass, using bubble sort to turn 1 5 2 9 into 1 2 5 9.

Explore the stack data structure by implementing a stack class with push and pop operations on a list, illustrating adding and removing the most recent value.

Master validating JSON format by matching opening and closing brackets with a stack, producing true or false via a Python-based algorithm.

Explore queue concepts by enqueuing at the back and dequeuing from the front, using Python lists or the collections deque for efficient front removals and optional stack behavior.

Explore reversing a queue without using the built-in method by popping values into a new queue with a while loop, then returning and printing the reversed order.

Explore the binary search tree data structure, observe how values branch to the left and right to maintain order, and implement search in code.

Learn to insert nodes into a binary search tree with a node class, left and right children, and a recursive insert function; visualize the structure with examples.

Explore in order traversal of a binary search tree using recursion, printing nodes left-root-right, and implement a recursive search function to locate values such as three, one, or six.

Learn to remove a value from a binary search tree by locating the node, handling cases, and replacing with the smallest right-subtree value, verified by printing the nodes in order.

Explore min heaps and max heaps, build a binary heap from inputs, and apply swaps to maintain heap order, with pop removing the smallest value.

Implement a min-heap in python by building a minyip class with push and pop, heapify up and down, and index helpers for parent, left, and right.

practice solving many coding questions to spot patterns, pause to attempt answers, and memorize solutions when needed; the next lecture introduces coding questions.