Computer science focuses on problem-solving through algorithms that can be transformed into efficient programs, reliant on knowledge of data structures and algorithms. Data structures are methods for storing and organizing data, classified into linear and non-linear types, each with specific characteristics and operations like traversing, insertion, deletion, updating, searching, and sorting. Understanding data structures enhances coding efficiency in terms of time, space, and resource management.

1. Data Structure

2. What is Computer Science:
Computer science deals with solving a problem correctly in the form of
Algorithm which then can be converted into a program
Problem → Solution (Algorithm) →Program (Efficient)

3. To write an efficient program we need knowledge of both, data structure and
algorithms.
ALGORITHM + DATA STRUCTURE = PROGRAM

4. Why we study data structure
• Objective is to teach you how to code efficiently
• What is meaning of efficiency (time, space, battery, system buses, registers)

5. What is Data Structure:
A data structure is a storage that is used to store and organize data. It
is a way of arranging data on a computer so that it can be accessed and
updated efficiently.

7. Classification of Data
There are many different data structures. Data structures have
their characteristics, features, applications, advantages,
and disadvantages.
non

8. Graph
Stack
Tree
Link List
Different data structures

9. Linear data structure: Data structure in which data elements are arranged sequentially or
linearly.
Examples:- array, stack, queue, linked list, etc.
Non-linear data structure: where data elements are not placed sequentially are called
non-linear data structures. In a non-linear data structure, we can’t traverse all the elements
in a single run only. Examples of non-linear data structures are trees and graphs.

10. Linear Data Structure types
• Static data structure: Static data structure has a fixed memory size. An
example of this data structure is an array.
• Dynamic data structure: In the dynamic data structure, the size is not
fixed. It can be randomly updated during the runtime. Examples of this data
structure are link list.

11. Operations on different Data Structure:
• Traversing
• Insertion
• Deletion
• Update
• Searching
• Sort

12. Operations on different Data Structure:
Traversing: Traversing a Data Structure means to visit the element
stored in it.

13. Operations on different Data Structure:
Insertion: Insertion means to add an element in the given data structure.

14. Operations on different Data Structure:
Deletion: Deletion means to delete an element in the given data
structure.

15. Operations on different Data Structure:
Update : It updates the data in the data structure.

16. Operations on different Data Structure:
Searching: Searching means to find a particular element in the given
data-structure.

17. Operations on different Data Structure:
Sort: Sorting data in a particular order (ascending or descending).