Data Structures and Algorithms with Python

Introduction to Data Structures and AlgorithmsOverview of Data Structures and Algorithms

Importance of Data Structures and Algorithms in Programming

How to choose the right Data Structure or Algorithm

Basic Python Concepts ReviewVariables and Data Types

Control Flow Statements

Functions

File Handling

Data StructuresArrays

Stacks and Queues

Linked Lists

Hash Tables

Trees

Types of TreesBinary Search Trees (BST)

Cartesian Trees (Treap)

BTrees

RedBlack Trees

Splay Trees

AVL Trees

KDimensional (KD) Trees

Trie Tree

Suffix Tree

Min Heap

Max Heap

Sorting AlgorithmQuick Sort

Merge Sort

Tim Sort

Heap Sort

Bubble Sort

Insertion Sort

Selection Sort

Tree Sort

Shell Sort

Bucket Sort

Radix Sort

Counting Sort

Cube Sort

Searching AlgorithmsLinear Search

Binary Search

Graph AlgorithmsDijkstra's Algorithm

Breadth First Search (BFS)

Depth First Search (DFS)

Algorithm Design TechniquesGreedy Algorithms

Dynamic Programming

Divide and Conquer

Backtracking

Randomized Algorithms

ConclusionRecap
Participants 681
Recap
In conclusion, this course on “Data Structures and Algorithms with Python” has provided you with a comprehensive introduction to the fundamental concepts of data structures and algorithms. You’ve learned about a wide range of data structures, including arrays, stacks, queues, linked lists, skip lists, hash tables, binary search trees, Cartesian trees, Btrees, redblack trees, splay trees, AVL trees, and KD trees. You’ve also learned about a variety of sorting and searching algorithms, as well as algorithm design techniques such as greedy algorithms, dynamic programming, divide and conquer, backtracking, and randomized algorithms.
You’ve also learned about Time and Space Complexity analysis, which will help you understand the tradeoffs between different data structures and algorithms. You’ve had the opportunity to practice and apply the concepts you’ve learned through handson exercises and examples.
By completing this course, you’ve acquired the knowledge and skills you need to become proficient in data structures and algorithms. With this knowledge, you’ll be able to choose the right data structure or algorithm for a given problem, and implement it efficiently and effectively in Python. This will help you to improve your skills as a developer and to prepare for a career in computer science or data science.
Thank you for taking this course, and I hope you’ve found it informative and helpful. I encourage you to continue to explore and practice data structures and algorithms, and to keep learning new skills as you continue to grow as a programmer.