Data Structures and Algorithms: In-Depth DSA using Python | Udemy


Data Structures and Algorithms: In-Depth DSA using Python | Udemy
English | Size: 10.38 GB
Genre: eLearning

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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