Introduction to Data Structures and Algorithms
Slides :- https://docs.google.com/presentation/d/1lAjAp8THovERcKYqEq6I8TW11598YCCiU8nT3GlXkN0/edit?usp=sharing
W3Schools :- https://www.w3schools.com/dsa/dsa_intro.php
Data Structures is about how data can be stored in different structures.
Algorithms is about how to solve different problems, often by searching through and manipulating data structures.
Theory about Data Structures and Algorithms (DSA) helps us to use large amounts of data to solve problems efficiently.
What are Data Structures?
A data structure is a way to store data.
We structure data in different ways depending on what data we have, and what we want to do with it.
Family Tree
Family tree
First, let's consider an example without computers in mind, just to get the idea.
If we want to store data about people we are related to, we use a family tree as the data structure. We choose a family tree as the data structure because we have information about people we are related to and how they are related, and we want an overview so that we can easily find a specific family member, several generations back.
With such a family tree data structure visually in front of you, it is easy to see, for example, who my mother's mother is—it is 'Emma,' right? But without the links from child to parents that this data structure provides, it would be difficult to determine how the individuals are related.
Data structures give us the possibility to manage large amounts of data efficiently for uses such as large databases and internet indexing services.
Data structures are essential ingredients in creating fast and powerful algorithms. They help in managing and organizing data, reduce complexity, and increase efficiency.
In Computer Science there are two different kinds of data structures.
Primitive Data Structures are basic data structures provided by programming languages to represent single values, such as integers, floating-point numbers, characters, and booleans.
Abstract Data Structures are higher-level data structures that are built using primitive data types and provide more complex and specialized operations. Some common examples of abstract data structures include arrays, linked lists, stacks, queues, trees, and graphs.
What are Algorithms?
An algorithm is a set of step-by-step instructions to solve a given problem or achieve a specific goal.
Pommes Frites Recipe
Pommes Frites Recipe
A cooking recipe written on a piece of paper is an example of an algorithm, where the goal is to make a certain dinner. The steps needed to make a specific dinner are described exactly.
Algorithms are fundamental to computer programming as they provide step-by-step instructions for executing tasks. An efficient algorithm can help us to find the solution we are looking for, and to transform a slow program into a faster one.
By studying algorithms, developers can write better programs.
Algorithm examples:
Finding the fastest route in a GPS navigation system
Navigating an airplane or a car (cruise control)
Finding what users search for (search engine)
Sorting, for example sorting movies by rating
The algorithms we will look at in this tutorial are designed to solve specific problems, and are often made to work on specific data structures. For example, the 'Bubble Sort' algorithm is designed to sort values, and is made to work on arrays.
Data Structures together with Algorithms
Data structures and algorithms (DSA) go hand in hand. A data structure is not worth much if you cannot search through it or manipulate it efficiently using algorithms, and the algorithms in this tutorial are not worth much without a data structure to work on.
DSA is about finding efficient ways to store and retrieve data, to perform operations on data, and to solve specific problems.
By understanding DSA, you can:
Decide which data structure or algorithm is best for a given situation.
Make programs that run faster or use less memory.
Understand how to approach complex problems and solve them in a systematic way.
Where is Data Structures and Algorithms Needed?
Data Structures and Algorithms (DSA) are used in virtually every software system, from operating systems to web applications:
For managing large amounts of data, such as in a social network or a search engine.
For scheduling tasks, to decide which task a computer should do first.
For planning routes, like in a GPS system to find the shortest path from A to B.
For optimizing processes, such as arranging tasks so they can be completed as quickly as possible.
For solving complex problems: From finding the best way to pack a truck to making a computer 'learn' from data.
DSA is fundamental in nearly every part of the software world:
Operating Systems
Database Systems
Web Applications
Machine Learning
Video Games
Cryptographic Systems
Data Analysis
Search Engines
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