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Data Structures and Algorithms in Python for Beginners

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Overview

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This beginner course introduces fundamental data structures and algorithms through Python implementations. It covers arrays, linked lists, trees, graphs, hash tables, searching, sorting, complexity analysis, and divide-and-conquer, greedy, and dynamic programming approaches.

Syllabus

Course Introduction.
Agenda.
Introduction to Data Structure.
Inbuilt and User-Defined Data Structure in Python.
Arrays Introduction.
Arrays Implementation.
Advantages and Disadvantages of Arrays.
Stack.
Advantages and Disadvantages of Stack.
Queue introduction.
Queue implementation.
Advantages and Disadvantages of Queue.
Linked list.
Advantages and Disadvantages of Linked List.
Binary tree introduction.
Binary tree implementation.
Advantages and Disadvantages of Binary Tree.
Binary search tree introduction.
Binary search tree implementation.
Advantages and Disadvantages of Binary search Tree.
Graphs introduction.
Breadth-first search implementation.
Depth-first search implementation.
Hash tables introduction.
Hashing implementation.
Algorithms introduction and algorithmic analysis.
Finding space and time complexity.
Linear Search.
Linear search implementation.
Complexity analysis of Linear Search.
Binary Search.
Binary search implementation.
Complexity analysis of Binary Search.
Insertion sort.
Insertion sort implementation.
Complexity analysis of Insertion sort.
Selection sort.
Selection sort implementation.
Complexity analysis of Selection sort.
Quicksort.
Quicksort implementation.
Complexity analysis of Quicksort.
Introduction to Divide and Conquer approach.
Merge sort.
merge sort implementation.
Introduction to Greedy's approach.
Prim's minimal Spanning Tree algorithm.
Prim's minimal Spanning Tree algorithm implementation.
Introduction to Dynamic Programming.
Tower of Hanoi.
Tower of Hanoi implementation.
Summary.

Taught by

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