Data Structures and Algorithms- In Depth using C#

Data Structures and Algorithms: In Depth using C#, available at $69.99, has an average rating of 4.49, with 397 lectures, based on 1784 reviews, and has 8711 subscribers.

You will learn about Understand Complexity of Algorithms ie Time and Space they take at runtime Learn and compare Algorithms used in Searching and Sorting Learn different Data Structures and how to use them in applications Learn how to Code and Implement various data structures and algorithms in C# This course is ideal for individuals who are Anyone who wants to learn Data Structures and Algorithms using C# It is particularly useful for Anyone who wants to learn Data Structures and Algorithms using C#.

Enroll now: Data Structures and Algorithms: In Depth using C#

Summary

Title: Data Structures and Algorithms: In Depth using C#

Price: $69.99

Average Rating: 4.49

Number of Lectures: 397

Number of Published Lectures: 397

Number of Curriculum Items: 397

Number of Published Curriculum Objects: 397

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will Learn

Understand Complexity of Algorithms ie Time and Space they take at runtime

Learn and compare Algorithms used in Searching and Sorting

Learn different Data Structures and how to use them in applications

Learn how to Code and Implement various data structures and algorithms in C#

Who Should Attend

Anyone who wants to learn Data Structures and Algorithms using C#

Target Audiences

Anyone who wants to learn Data Structures and Algorithms using C#

This course will help you in better understanding of the basics of Data Structures and how algorithms are implemented in C# programming language. This course consists of lectures on data structures and algorithms which covers the computer science theory + implementation of data structures in C#. This course will also help students to face interviews confidently at the top technology companies. This course is like having personal tutors to teach you about data structures and algorithms.

There’s tons of concepts and content in this course. To begin the course:

We have a discussion of why we need data structures and why we need to learn Algorithms

Then we move on to discuss Analysis of Algorithms ie Time and Space complexity, though the Asymptotic Notation ie Big O, Omega and Theta are taken up at the end of this course so that you do not get confused and concentrate on understanding the concepts of data structures.

Then we get to the essence of the course; algorithms and data structures. Each of the specific algorithms and data structures is divided into two sections. Theory lectures and implementation of those concepts in C#. We then move on to learn:

1. Analysis of Algorithms

2. Recursion

3. Searching Algorithms

4. Sorting Algorithms

5. Linked List

6. Stacks

7. Queues & Deques

8. Trees, Binary Trees & Binary Search Trees

9. Balanced Search Trees

10. Heaps

11. Hashing

12. Graphs & Graph Traversal Algorithms (Breadth-First Search & Depth First Search)

Again, each of these sections includes theory lectures covering Data structures & their Abstract Data Types and Algorithms. Plus the implementation of these topics in C#.

Course Curriculum

Chapter 1: Course Overview

Lecture 1: Course Outcomes & Curriculum

Lecture 2: Why we Need Data Structures ?

Lecture 3: Why Learn Algorithms ?

Lecture 4: Abstract Data Type (ADT)

Lecture 5: Visual Studio C# : Execution Environment

Chapter 2: Analysis of Algorithms

Lecture 1: Time Complexity

Lecture 2: Order of Growth

Lecture 3: Asymptotic Analysis

Lecture 4: Big-Oh Notation

Lecture 5: Big Omega Notation

Lecture 6: Big Theta Notation

Lecture 7: Performance Summary

Lecture 8: Space Complexity

Chapter 3: Recursion and Analysis of Recursive Functions

Lecture 1: How Recursion Works ?

Lecture 2: Lab: Iteration Vs Recursion – Implementation

Lecture 3: Time Complexity of Recursion – Recurrence Relation

Lecture 4: Recurrence Relation – Another example

Lecture 5: Tail and Head Recursion

Lecture 6: Tree Recursion

Lecture 7: Indirect Recursion

Lecture 8: Sum of N Natural Numbers

Lecture 9: Lab: Sum of N Numbers – Implementation

Lecture 10: Factorial

Lecture 11: Lab: Factorial – Implementation

Chapter 4: Searching Algorithms

Lecture 1: Linear Search Algorithm

Lecture 2: Lab: Linear Search – Implementation

Lecture 3: Binary Search Iterative Algorithm

Lecture 4: Lab: Binary Search using Iterations – Implementation

Lecture 5: Binary Search Recursive Algorithm

Lecture 6: Lab: Binary Search using Recursion – Implementation

Chapter 5: Sorting Algorithms

Lecture 1: Sorting Introduction

Lecture 2: Stable and Unstable Sorting

Lecture 3: Selection Sort – How does it Work ?

Lecture 4: Selection Sort – Algorithm and Analysis

Lecture 5: Lab: Selection Sort – Implementation

Lecture 6: Insertion Sort – How does it Work ?

Lecture 7: Insertion Sort – Algorithm and Analysis

Lecture 8: Lab: Insertion Sort – Implementation

Lecture 9: Bubble Sort – How does it Work ?

Lecture 10: Bubble Sort – Algorithm and Analysis

Lecture 11: Lab: Bubble Sort – Implementation

Lecture 12: Shell Sort – How does it Work ?

Lecture 13: Shell Sort – Algorithm and Analysis

Lecture 14: Lab: Shell Sort – Implementation

Lecture 15: Merge Sort – How does it Work ?

Lecture 16: Merge Sort – Algorithm

Lecture 17: Merging – Algorithm

Lecture 18: Merge Sort – Complexity Analysis

Lecture 19: Lab: Merge Sort – Implementation

Lecture 20: Quick Sort – How does it Work ?

Lecture 21: Quick Sort – Algorithm

Lecture 22: Quick Sort – Complexity Analysis

Lecture 23: Lab: Quick Sort – Implementation

Lecture 24: Summary of Complexities – Sorting Algorithms

Chapter 6: Linked List

Lecture 1: Why do we use Linked List ?

Lecture 2: Creating Node of Linked List

Lecture 3: Playing with the links of Linked List

Lecture 4: How to Create Linked List ?

Lecture 5: Displaying or Traversing Linked List

Lecture 6: Lab: Creating and Displaying Linked List – Implementation

Lecture 7: Insert Element at the Beginning of Linked List

Lecture 8: Lab: Insert Element at the Beginning of Linked List – Implementation

Lecture 9: Insert Element Anywhere in between the Linked List

Lecture 10: Lab: Insert Element Anywhere in Between the Linked List – Implementation

Lecture 11: Delete Element at Beginning of Linked List

Lecture 12: Lab: Delete Element at Beginning of the Linked List – Implementation

Lecture 13: Delete Element at End of Linked List

Lecture 14: Lab: Delete Element at End of Linked List – Implementation

Lecture 15: Delete Element Anywhere in between Linked List

Lecture 16: Lab: Delete Element Anywhere in between Linked List – Implementation

Lecture 17: Searching Element in Linked List

Lecture 18: Lab: Searching the Linked List – Implementation

Lecture 19: 24. Exercise Solution Inserting Elements in Sorted Order

Chapter 7: Circular Linked List

Lecture 1: What is Circular Linked List ?

Lecture 2: Creating Circular Linked List

Lecture 3: Traversing Circular Linked List

Lecture 4: Lab: Creating and Displaying Circular Linked List – Implementation

Lecture 5: Insert Element at the Beginning of Circular Linked List

Lecture 6: Lab: Insert Element at the Beginning of Circular Linked List – Implementation

Lecture 7: Insert Element Anywhere in between the Circular Linked List

Lecture 8: Lab: Insert Element Anywhere in Between the Circular Linked List -Implementation

Lecture 9: Delete Element at Beginning of Circular Linked List

Lecture 10: Lab: Delete Element at Beginning of the Circular Linked List – Implementation

Lecture 11: Delete Element at End of Circular Linked List

Lecture 12: Lab: Delete Element at End of Circular Linked List – Implementation

Lecture 13: Delete Element Anywhere in between Circular Linked List

Lecture 14: Lab: Delete Element Anywhere in between Circular Linked List – Implementation

Chapter 8: Doubly Linked List

Lecture 1: What is Doubly Linked List ?

Lecture 2: Creating Node of Doubly Linked List

Lecture 3: Playing with links of Doubly Linked List

Lecture 4: Creating Doubly Linked List

Lecture 5: Traversing Doubly Linked List

Instructors

Syed Mohiuddin
Instructor

Rating Distribution

1 stars: 17 votes

2 stars: 24 votes

3 stars: 187 votes

4 stars: 691 votes

5 stars: 873 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!