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## Data Structure Algorithms For Beginners For Data Science

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### Algorithms and Data Structures What will you learn?

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### DATA STRUCTURE ALGORITHMS FOR BEGINNERS FOR DATA SCIENCE Syllabus

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DATA STRUCTURE ALGORITHMS FOR BEGINNERS FOR DATA SCIENCE

Algorithms and Data Structures Online Training Institute

Graduates and Technology Aspirants

Both Classroom and Online Classes

Week Days and Week Ends

Fast Track and Regular 60 Days

•A Beginner’s Guide to Algorithms and Data Structures Coding from scratch

•How to create your own Algorithms and Data Structures components from scratch.

•Learning and Creating a complete Algorithms and Data Structures project in depth

•What is Algorithms and Data Structures and How to Build apps using Algorithms and Data Structures.

•Learn A to Z of Algorithms and Data Structures from Basic to ADVANCE level.

•Learn Algorithms and Data Structures the Fast and Easy Way With This Popular Bundle Course!

•Learn Algorithms and Data Structures with hands-on coding exercises. Take your Algorithms and Data Structures Skill to the next level

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•Course delivery through industry experts

•Fast Track course available with best Fees

•Create hands-on projects at the end of the course

• Greater productivity and increased workforce morale

•Courseware includes reference material to maximize learning.

•Curriculum based on course outlines defined by in-demand skills in Python.

•We do Schedule the sessions based upon your comfort by our Highly Qualified Trainers and Real time Experts

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•Java Developer, Php Mysql, Zend 2.0, java j2ee struts hibernate spring, iOS, Android, html

•Microsoft Azure, Azure, Sql Azure, Cloud Computing, Cloud Testing, SQL, Cognos Framework Manager, Query Studio, Oracle, Business Objects, Issue Resolution

•Python, React, Javascript, Html, Css, Web Technologies, Front End Developer, Backend Developer, Mysql, Mongodb

•Spring, Hibernate, Java, Dot Net, Dotnet MVC, Android, iOS, Dot net developer, Android Developer, Manual Testing, Embedded, Telecom

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•Introduction- Part 2 – Data Structure

•Introduction Part 3: Data structure and algorithm

•Introduction Part 4: Data structure and algorithm

•Introduction Part 5: Data structure and algorithm

•Introduction Part 6: Data structure and algorithm

•Recursion – Data Structures

•Recursion – Introduction

•Why we need recursion?

•How recursion works internally ?

•Example of Recursion – 1

•Recursion vs Iteration

•Advantage and disadvantage of Recursion

•Recursion- Example 1

•Recursion – Example 2

•Algorithm Run time

•Algorithm Run time – Introduction

•Algorithm run time notation

•Time complexity

•Example – 1: Algorithm run time

•Example – 2: Algorithm run time

•Example – 3: Algorithm run time

•Python programming – Algorithm run time

•Array – Data structure

•Array Introduction

•1D array with example

•2D Array

•Stack – Data Structure

•Stack – Introduction

•Stack – Rest of the concepts

•Stack Program Introduction

•Stack – Other functionality program

•Queue – Data Structure

•Queue – Introduction

•Queue creation and Enqueue

•Linear Queue

•Linear Queue – Program Basic

•BFS – Part 1

•BFS – Part 2

•Circular Queue – Introduction

•Circular Queue – Remaining topic

•Circular Queue – Basic program

•Linked List

•Linked List – Introduction

•Array vs Linked List

•Types of Linked list

•Memory Allocation in Linked List

•Creation of Linked List

•Insertion in Linked List

•Traverse and search of Linked List

•Deletion of Linked List

•Creation of circular linked list

•Insertion of Circular linked list

•Insertion Algorithm in Circular Linked list

•Traverse and search of Circular Linked List

•Deletion of Circular Linked List

•Creation of Doubly linked list

•Insertion of Doubly linked list

•Insertion Algorithm in Doubly Linked list

•Traverse and search of Doubly Linked List

•Deletion of Doubly Linked List

•Creation of Doubly Circular linked list

•Insertion in Doubly Circular Linked list

•Insertion Algorithm in Doubly Circular Linked list

•Traverse and search of Doubly Circular Linked List

•Tree

•Tree Introduction

•Why we need Tree Data structure?

•Tree Terminology – Part 1

•Tree Terminology – Part 2

•Introduction to Binary tree

•Types of Binary Tree

•Binary Tree representation

•Creating Binary Tree using Linked List

•Pre-Order traversal using Linked List

•In-Order Traversal using Linked List

•Post-Order Traversal using Linked List

•Level-Order Traversal

•Insertion in Binary Tree using Linked List

•Search in Binary Tree using Linked List

•Deletion in Binary Tree using Linked List

•Delete Binary Tree using Linked List

•Creation of Binary Tree using Arrays

•Insertion in Binary Tree using Array

•Insertion Algorithm in Binary Tree using Array

•In-Order Traversal using Array

•Pre-Order traversal using Array

•Post-Order Traversal using Array

•Deletion in Binary tree using array

•Delete Binary tree using Array

•Binary Search Tree

•Binary Search Tree – Introduction 1

•Binary Search Tree – Introduction 2

•Creation of Binary Search Tree

•Traversal of Binary Search Tree

•Insertion in Binary Search Tree

•Insertion algorithm in Binary search tree

•Deletion of Binary search Tree

•Delete Binary search Tree

•AVL Tree

•AVL Tree – Introduction

•What is AVL Tree?

•Creation and search of AVL Tree

•Traversal of AVL Tree

•Insertion in AVL Tree

•Left-Left Violation in AVL tree

•Right-Right Violation in AVL Tree

•Left-Right Violation in AVL Tree

•Right-Left Violation in AVL Tree

•Deletion in AVL Tree

•Heap in Data Structure and Algorithm

•Binary Heap- Introduction

•Types of Heap Tree

•Creation of Heap in Data Structure

•Peek and Search using Heap

•Insertion in Heap Tree

•Deletion of Heap Tree

•Delete Heap tree

•Trie in Data Structure and Algorithm

•Trie – Introduction

•Insertion in Trie

•Deletion in Trie

•Hashing in Data Structure

•Hashing – Introduction

•Hashing – Introduction 2

•Collision in Hashing

•Collision resolution – Part 1

•Collision resolution – Part 2

•When Collision is Full

•Comparison of Collision Technique

•Application of Hashing

•Sorting in Data Structure

•Sorting – Introduction and Terminalogy

•Bubble Sort

•Selection Sort

•Insertion Sort

•Bucket Sort

•Merge Sort

•Quick Sort – Part 1

•Quick Sort – Part 2

•Heap Sort – Part 1

•Heap Sort – Part 2

•Graph in Data Structure and Algorithm

•Graph Introduction

•Graph Terminology

•Types of Graph

•DFS

•BFS vs DFS

•Topological Sort – Part 1

•Topological Sort – Part 2

•Single Source shortest Path – Explanation

•Single Source shortest Path – Algorithm

•Disadvantage of BFS and DFS – SSSP

•Dijkstra’s Algorithm

•Bellmann Ford

•Bellmann Ford Algorithm

•Bellmann Ford Negative cycle

•All source shortest path algorithm

•Dry run of All source shortest path algorithm

•Minimum spanning tree

•Disjoint set

•Kruskal Algorithm

•Prims Algorithm

•Magic Framework

•Greedy Algorithm

•Greedy Algorithm – Introduction

•Greedy Algorithm – Sorting

•Greedy Algorithm – Minimum Spamming Tree

•Activity selection problem

•Coin change problem

•Fractional Knapsack

•Divide and Conquer

•Divide and Conquer- Introduction

•Binary search using divide and conquer algorithm

•Quick sort using divide and conquer algorithm

•Merge sort using divide and conquer algorithm

•Fibonacci series using divide and conquer algorithm

•House Thief problem using divide and conquer algorithm

•Number factor problem using divide and conquer

•Convert from one string to another using divide and conquer algorithm

•Dynamic programming

•Dynamic programming – Introduction

•Top-down approach

•Bottom-up approach using Dynamic programming

•Merge sort using Dynamic programming

•House thief problem using Dynamic programming

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