Learn Python Data Structures, Algorithms (DSA) with Animated Examples, includes Dynamic Programming, Backtracking etc.

What you'll learn
Learn Data Structures, Abstract Data Types and their implementation in Python
Implementation of Searching Algorithms in Python
Implementation of Stacks, Queues, Linked List, Binary Trees, Heaps and Graphs in Python
Implementation of Binary Tree Traversal Techniques in Python
Graph traversals techniques ie Depth First Search and Breadth-First Search in Python
Implementation of Sorting Algorithms in Python
Enhance Analytical Skill and efficiently use searching and sorting algorithms in real applications

Requirements
Prior knowledge of Programming any high level language
Basic knowledge of Python Programming

Description
This course will help you in better understanding of the basics of Data Structures and how algorithms are implemented in Python. This course consists of Videos which covers the theory concepts + implementation in python. There's tons of concepts and content in this course:Basics of data structures & AlgorithmsAnalysis of Algorithms (Big O, Time and Space complexity) Recursion & Analysis of Recursive AlgorithmsSearching AlgorithmsSorting AlgorithmsLinked ListStacksQueuesBinary TreesBinary Search TreesBalanced Binary Search TreesPriority Queues and HeapsHashingGraphsGraph Traversal AlgorithmsFollowed by Advanced Topics of Algorithms:Sets and Disjoint SetsDivide and Conquer Approach - IntroductionDivide and Conquer - Binary SearchDivide and Conquer - Finding Maximum and MininumDivide and Conquer - Merge SortDivide and Conquer - Quick SortDivide and Conquer - Selection AlgorithmDivide and Conquer - Strassens Matrix MultiplicationDivide and Conquer - Closest PairDivide and Conquer - Convex HullGreedy Method - IntroductionGreedy Method - Knapsack ProblemGreedy Method - Job Sequencing with DeadlinesGreedy Method - Mininum Cost Spanning Tree (Prim's & Kruskal's Algorithms)Greedy Method - Optimal Storage on TreesGreedy Method - Optimal Merge PatternGreedy Method - Single Source Shortest Path (Dijkstra's Algorithm)Dynamic Programming - IntroductionDynamic Programming - Multistage GraphsDynamic Programming - All Pairs Shortest PathDynamic Programming - Single Source Shortest PathDynamic Programming - Optimal Binary Search TreesDynamic Programming - 0/1 Knapsack ProblemDynamic Programming - Reliability DesignDynamic Programming - Travelling Salespersons ProblemBacktracking - IntroductionBacktracking - n-Queesn ProblemBacktracking - Sum of Subsets ProblemBacktracking - Graph Coloring ProblemBacktracking - Hamiltonian Cycles ProblemBacktracking - 0/1 Knapsack ProblemBranch & Bound - IntroductionBranch & Bound - n-Queens ProblemBranch & Bound - Job Sequencing ProblemBranch & Bound - 0/1 Knapsack ProblemAgain, each of these sections includes detailed videos tutorial.

Who this course is for:
Students who want to have better understanding of Data Structures, Python programmers curious about Data Structures, IT Professional experimenting implementation of Data Structures in Python

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