Introduction to Data Structures Algorithms in Java_1

Introduction to Data Structures & Algorithms in Java, available at $69.99, has an average rating of 4.46, with 104 lectures, 10 quizzes, based on 3480 reviews, and has 25374 subscribers.

You will learn about Be able to know and implement various data structures and algorithms Be able to write your own algorithms and understand if their running time is good or bad This course is ideal for individuals who are Anyone who wants to learn data structures and algorithms (introductory) or Anyone appearing for interviews, can be used to understand from grounds up, or as a quick revision It is particularly useful for Anyone who wants to learn data structures and algorithms (introductory) or Anyone appearing for interviews, can be used to understand from grounds up, or as a quick revision.

Enroll now: Introduction to Data Structures & Algorithms in Java

Summary

Title: Introduction to Data Structures & Algorithms in Java

Price: $69.99

Average Rating: 4.46

Number of Lectures: 104

Number of Quizzes: 10

Number of Published Lectures: 103

Number of Published Quizzes: 10

Number of Curriculum Items: 114

Number of Published Curriculum Objects: 113

Original Price: $54.99

Quality Status: approved

Status: Live

What You Will Learn

Be able to know and implement various data structures and algorithms

Be able to write your own algorithms and understand if their running time is good or bad

Who Should Attend

Anyone who wants to learn data structures and algorithms (introductory)

Anyone appearing for interviews, can be used to understand from grounds up, or as a quick revision

Target Audiences

Anyone who wants to learn data structures and algorithms (introductory)

Anyone appearing for interviews, can be used to understand from grounds up, or as a quick revision

This course introduces some basic data structures (arrays, linked lists, stacks, queues, trees and heaps) and algorithms (various sorting algorithms, and algorithms for operations on binary search trees and heaps). We will also cover recursion in this course. Use of graphics and animations makes the lectures very easy to understand and digest. After taking this course, you will loose your fear for data structures and algorithms.

Course Curriculum

Chapter 1: Introduction to Algorithms

Lecture 1: Introduction

Lecture 2: Euclids algorithm

Lecture 3: Bubble Sort algorithm

Lecture 4: Why study data structures & algorithms

Lecture 5: Correctness of an algorithm

Chapter 2: Analysis of Algorithms

Lecture 1: Note on this section

Lecture 2: Introduction

Lecture 3: How to calculate the time complexity

Lecture 4: The RAM model of computation

Lecture 5: Time complexity of Bubble sort algorithm

Lecture 6: Pseudo code : Bubble sort algorithm

Lecture 7: The Big O notation

Lecture 8: Using Big O notation : Examples

Lecture 9: Comparison of running times

Chapter 3: Basic Sorting and Search Algorithms

Lecture 1: Selection Sort

Lecture 2: Selection Sort : Pseudocode

Lecture 3: Introduction to Insertion Sort

Lecture 4: Applying Insertion Sort algorithm to cue balls

Lecture 5: Insertion Sort: Pseudocode

Lecture 6: O(n2) sorting algorithms – Comparison

Lecture 7: In place sorting

Lecture 8: Stable Vs Unstable Sorts

Lecture 9: Searching elements in an un ordered array

Lecture 10: Searching elements in an ORDERED array

Lecture 11: Searching elements in an ORDERED array – contd.

Lecture 12: Inserting and Deleting items in an ORDERED array

Lecture 13: Sorting any type of object

Lecture 14: Assignment

Chapter 4: Linked Lists

Lecture 1: What is a Linked List?

Lecture 2: Implementing a Linked List in Java

Lecture 3: Inserting a new Node

Lecture 4: Length of a Linked List

Lecture 5: Deleting the head node

Lecture 6: Searching for an Item

Lecture 7: Using java generics to parameterize the LinkedList

Lecture 8: Doubly Ended Lists

Lecture 9: Inserting data in a sorted Linked List

Lecture 10: Doubly Linked List

Lecture 11: Insertion Sort revisited

Lecture 12: Assignment

Chapter 5: Stacks and Queues

Lecture 1: Stacks

Lecture 2: Abstract Data Types

Lecture 3: Implementing Stacks using Arrays

Lecture 4: Queues

Lecture 5: Queues using Arrays

Lecture 6: Double Ended Queues

Lecture 7: Double Ended Queues using Arrays

Lecture 8: Assignment

Chapter 6: Recursion

Lecture 1: Introduction

Lecture 2: Understanding Recursion

Lecture 3: Tail recursion

Lecture 4: Tower of Hanoi

Lecture 5: Tower of Hanoi – Implementation

Lecture 6: Merge Sort

Lecture 7: Merge Sort – Pseudocode

Lecture 8: Merge Step – Pseudocode

Lecture 9: Time Complexity of Merge Sort

Lecture 10: Assignment

Chapter 7: Binary Search Trees

Lecture 1: The Tree Data structure

Lecture 2: Binary Trees

Lecture 3: Binary Search Trees

Lecture 4: Finding an item in a Binary Search Tree

Lecture 5: Implementing the find method

Lecture 6: Inserting an item in a Binary Search Tree

Lecture 7: Deleting an Item : Case 1

Lecture 8: Deleting an Item – Case 2

Lecture 9: Deleting an Item – Case 3

Lecture 10: Deleting an Item – Soft Delete

Lecture 11: Finding smallest & largest values

Lecture 12: Tree Traversal : In Order

Lecture 13: Tree Traversal : Pre Order

Lecture 14: Tree Traversal : Post Order

Lecture 15: Unbalanced Trees Vs Balanced Trees

Lecture 16: Height of a Binary Tree

Lecture 17: Time Complexity of Operations on Binary Search Trees

Lecture 18: Assignment

Chapter 8: More Sorting Algorithms

Lecture 1: Introduction

Lecture 2: QuickSort

Lecture 3: QuickSort: The partition step

Lecture 4: Shell Sort

Lecture 5: Shell Sort: Example

Lecture 6: Counting Sort

Lecture 7: Radix Sort

Lecture 8: Bucket Sort

Instructors

Raghavendra Dixit
Dizauvi Learning Solutions

Rating Distribution

1 stars: 92 votes

2 stars: 110 votes

3 stars: 456 votes

4 stars: 1255 votes

5 stars: 1567 votes

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