Data Structures and Algorithms: In-Depth DSA using Python | Udemy
English | Size: 10.38 GB
Genre: eLearning[/center]
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
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 & Algorithms
Analysis of Algorithms (Big O, Time and Space complexity)
Recursion & Analysis of Recursive Algorithms
Searching Algorithms
Sorting Algorithms
Linked List
Stacks
Queues
Binary Trees
Binary Search Trees
Balanced Binary Search Trees
Priority Queues and Heaps
Hashing
Graphs
Graph Traversal Algorithms
Followed by Advanced Topics of Algorithms:
Sets and Disjoint Sets
Divide and Conquer Approach - Introduction
Divide and Conquer - Binary Search
Divide and Conquer - Finding Maximum and Mininum
Divide and Conquer - Merge Sort
Divide and Conquer - Quick Sort
Divide and Conquer - Selection Algorithm
Divide and Conquer - Strassens Matrix Multiplication
Divide and Conquer - Closest Pair
Divide and Conquer - Convex Hull
Greedy Method - Introduction
Greedy Method - Knapsack Problem
Greedy Method - Job Sequencing with Deadlines
Greedy Method - Mininum Cost Spanning Tree (Prim's & Kruskal's Algorithms)
Greedy Method - Optimal Storage on Trees
Greedy Method - Optimal Merge Pattern
Greedy Method - Single Source Shortest Path (Dijkstra's Algorithm)
Dynamic Programming - Introduction
Dynamic Programming - Multistage Graphs
Dynamic Programming - All Pairs Shortest Path
Dynamic Programming - Single Source Shortest Path
Dynamic Programming - Optimal Binary Search Trees
Dynamic Programming - 0/1 Knapsack Problem
Dynamic Programming - Reliability Design
Dynamic Programming - Travelling Salespersons Problem
Backtracking - Introduction
Backtracking - n-Queesn Problem
Backtracking - Sum of Subsets Problem
Backtracking - Graph Coloring Problem
Backtracking - Hamiltonian Cycles Problem
Backtracking - 0/1 Knapsack Problem
Branch & Bound - Introduction
Branch & Bound - n-Queens Problem
Branch & Bound - Job Sequencing Problem
Branch & Bound - 0/1 Knapsack Problem
Again, 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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