Data Structures

A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this online course, we consider the common data structures that are used in various computational problems.

You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments.

This will help you to understand what is going on inside a particular built-in implementation of a data structure and what to expect from it. You will also learn typical use cases for these data structures.

Data-Structure Training Course Objective:

• 1. To provide the knowledge of basic data structures and their implementations.
• 2. To understand importance of data structures in context of writing efficient programs.
• 3. To develop skills to apply appropriate data structures in problem solving.

Why This Course is Required:

If the course relates to your future or current career, consider discussing your professional goals and how the course is aligned with them.

Be specific about how you believe this course prepared you for your profession and what you learned.

Our Training Methodology:

Canter technologies is the best Data-Structure training institute in Guntur. Here we provide Data-Structure Programming Training in Guntur with certification. Our Data-Structure Programming course content created by industry experts, to fulfill industry expectations.

They will provide in depth training on Data-Structure Programming in Guntur. Data-Structure Programming training in Guntur will take from 30-45 days to become expert in Data-Structure programming.

We are best Data-Structure language training institute in Guntur hear you learn concepts of Basic Introduction of Data-Structure, Arrays and List, Stacks, Queues and Hashing, Trees, Graphs in Data-Structure programming training institute in Guntur.

Data-Structure Language Course Objectives:

• 1. Arrays and List: Array:
• Definition
• Representation
• Address Calculation
• Searching:
• Linear search
• Binary search
• Sorting: Bubble sort, Insertion sort, Selection sort, Radix sort, Shell sort
• List: Introduction
• Implementation as Linked list
• Circular linked List
• Doubly linked list
• Applications of linked list.
• 2. Stacks:
• Definition
• Representations: static and dynamic, Implementation of stack
• Applications of stack:
• Polish notation representation and conversion
• Tower of Hanoi problem
• Implementation of recursion
• Quick sort and Merge sort.
• 3. Queues and Hashing:
• Definition
• Representations
• Static and dynamic
• Circular Queue
• Double ended Queue
• Priority Queue
• applications of queues.
• Hash Structures: Representation
• Search and Implementation and other issues.
• 4. Trees:
• Definition
• Basic terminology
• Binary tree
• Complete Binary Tree
• representations: Static and dynamic, Traversal techniques in binary tree
• Heap tree & its applications
• Binary Search tree
• AVL tree
• M-way search trees
• B-tree & its variations.
• 5. Graphs:
• Definition
• Basic terminology
• Graph Types
• Representations: static, dynamic; Implementations
• Searching in graphs – BFS, DFS
• Shortest path in graphs
• Applications.