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Advanced Data Structures and Algorithms in Python ( DSA )

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Advanced Data Structures and Algorithms in Python ( DSA ), available at $59.99, has an average rating of 4.7, with 66 lectures, based on 20 reviews, and has 485 subscribers.

You will learn about Understand various data structures and algorithms (DSA) through animations Get the ability to implement different algorithms in Python Get the confidence to face programming interviews Learn theory and implementation of AVL Trees, B Trees, Threaded Binary Trees and Expression Trees Graph, traversal and shortest path algorithms This course is ideal for individuals who are Professional Programmers wanting to write effective code or Programmers looking for jobs or Computer Science students having Data Structures as part of their curriculum or Non Computer science students wanting to enter IT industry It is particularly useful for Professional Programmers wanting to write effective code or Programmers looking for jobs or Computer Science students having Data Structures as part of their curriculum or Non Computer science students wanting to enter IT industry.

Enroll now: Advanced Data Structures and Algorithms in Python ( DSA )

Summary

Title: Advanced Data Structures and Algorithms in Python ( DSA )

Price: $59.99

Average Rating: 4.7

Number of Lectures: 66

Number of Published Lectures: 66

Number of Curriculum Items: 66

Number of Published Curriculum Objects: 66

Original Price: $129.99

Quality Status: approved

Status: Live

What You Will Learn

  • Understand various data structures and algorithms (DSA) through animations
  • Get the ability to implement different algorithms in Python
  • Get the confidence to face programming interviews
  • Learn theory and implementation of AVL Trees, B Trees, Threaded Binary Trees and Expression Trees
  • Graph, traversal and shortest path algorithms

Who Should Attend

  • Professional Programmers wanting to write effective code
  • Programmers looking for jobs
  • Computer Science students having Data Structures as part of their curriculum
  • Non Computer science students wanting to enter IT industry

Target Audiences

  • Professional Programmers wanting to write effective code
  • Programmers looking for jobs
  • Computer Science students having Data Structures as part of their curriculum
  • Non Computer science students wanting to enter IT industry

This “Advanced Data Structures and Algorithms In Python” course is thoroughly detailed and uses lots of animations to help you visualize the concepts.

Instructor is author of popular books “C In Depth” and “Data Structures Through C In Depth” helped 250,000+ students & professionals.

This “Advanced Data Structures and Algorithms in Python” tutorial provides a comprehensive explanation of different types of graph and various graph algorithms. Throughout the course a step by step approach is followed to make you understand different algorithms. Through this course you can build a strong foundation and it will help you to crack Data Structures and Algorithms in Python coding interviews questions and work on projects. Good foundation on Data Structures and Algorithms in Python interview topics helps you to attempt tricky interview questions.

This Data Structures and Algorithms using Python course covers following topics with Python implementation :

Trees : AVL Tree, Threaded Binary Tree, Expression Tree, B Tree explained and implemented in Python

Graphs : Adjacency matrix, Adjacency list, Path matrix, Warshall’s Algorithm, Traversal, Breadth First Search (BFS), Depth First Search (DFS),

Dijkstra’s Shortest Path Algorithm, Prim’s Algorithm and Kruskal’s Algorithm for minimum spanning tree

Here is the course content-

  • AVL Tree

  • Threaded Binary Tree

  • Expression Tree

  • B Tree

  • Graph

  • Traversal in Graph

  • Shortest Paths in Graph

  • Minimum Spanning Tree of a Graph

The Data Structures and Algorithms with Python course is broken down into easy to assimilate short lectures and complete working programs are shown for each concept that is explained. The algorithms and examples are explained with figures and animations to simplify the learning of this complex topic.  You will see code implementation of different data structures in Python and algorithms are explained in step-wise manner.

In this Data Structures and Algorithms through Python course, Python programs are used for implementing various concepts, but you can easily code them in any other programming language like Java, C++, C#.

This “Data Structures and Algorithms In Python” online course on udemy will help software developers to refresh the concepts studied in Data Structures and Algorithms In Python books / pdf and also to students learning from referred books / pdf.

So what are you waiting for, click on Buybutton to enroll now and start learning.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction to Advanced Data Structures and Algorithms Through Python In Depth

Chapter 2: AVL Tree

Lecture 1: Important : Source Code Repository required for course

Lecture 2: Introduction

Lecture 3: Rotations

Lecture 4: Insertion in AVL Tree -1

Lecture 5: Insertion in AVL Tree -2

Lecture 6: Insertion in AVL Tree -3

Lecture 7: Insertion in AVL Tree -4

Lecture 8: Examples of insertion in AVL Tree

Lecture 9: Deletion in AVL Tree – 1

Lecture 10: Deletion in AVL Tree – 2

Lecture 11: Deletion in AVL Tree – 3

Lecture 12: Examples of deletion in AVL Tree

Lecture 13: Your Review Matters!

Chapter 3: Threaded Binary Tree

Lecture 1: Introduction

Lecture 2: Insertion

Lecture 3: Deletion

Chapter 4: Expression Tree

Lecture 1: Introduction

Lecture 2: Constructing and Evaluating an Expression Tree

Lecture 3: Implementation of Expression Tree

Chapter 5: B tree

Lecture 1: Introduction

Lecture 2: Inorder Traversal

Lecture 3: Searching

Lecture 4: Insertion

Lecture 5: Implementation of Insertion -1

Lecture 6: Implementation of Insertion -2

Lecture 7: Deletion

Lecture 8: Examples of Deletion from Leaf Node

Lecture 9: Examples of Deletion from Non-Leaf Node

Lecture 10: Implementation of Deletion

Chapter 6: Graph

Lecture 1: Introduction

Lecture 2: Terminology

Lecture 3: Cycles

Lecture 4: Connectivity in Undirected Graph

Lecture 5: Connectivity in Directed Graphs

Lecture 6: Tree and Forest

Lecture 7: Representation of Graph : Adjacency Matrix

Lecture 8: Adjacency Matrix in Python

Lecture 9: Adjacency List in Python

Lecture 10: Transitive closure of a directed graph and Path Matrix

Lecture 11: Warshall’s Algorithm

Lecture 12: Warshall’s Algorithm in Python

Chapter 7: Traversal in Graph

Lecture 1: Introduction

Lecture 2: Breadth First Search

Lecture 3: Implementation of Breadth First Search

Lecture 4: Finding Shortest path in an unweighted graph

Lecture 5: BFS Spanning Tree

Lecture 6: BFS in Undirected Graphs : Finding Connected Components

Lecture 7: Depth First Search

Lecture 8: Implementation of Depth First Search through Stack

Lecture 9: Recursive Implementation of Depth First Search

Lecture 10: Classification of Edges in DFS of Directed Graph

Lecture 11: Classification of Edges in DFS of Undirected Graph

Chapter 8: Shortest Paths in Graph

Lecture 1: Shortest Path Problem

Lecture 2: Dijkstra’s Algorithm

Lecture 3: Dijkstra’s Algorithm : Example

Lecture 4: Dijkstra’s Algorithm in Python

Chapter 9: Minimum Spanning Tree of a Graph

Lecture 1: Introduction

Lecture 2: Prim's Algorithm

Lecture 3: Prim's Algorithm : Example

Lecture 4: Prim's Algorithm in Python

Lecture 5: Kruskal's Algorithm

Lecture 6: Kruskal's Algorithm : Example

Lecture 7: Implementation of Kruskal's Algorithm

Lecture 8: Kruskal's Algorithm in Python

Chapter 10: Bonus Lecture

Lecture 1: Recommended Course and Offer on my other courses

Instructors

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  • 3 stars: 1 votes
  • 4 stars: 5 votes
  • 5 stars: 14 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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