Summary DATA STRUCTURE AND ALGORITHM PART 1

DATA STRUCTURE AND ALGORITHM
#LECTURE 1


Introduction to Data Structures &
Algorithms
CodeWithHarry
Course Introduction
This course is designed for placement preparation and will
mainly cover data structures and algorithms using C and C++.
Even if you do not know C++, you will still be able to follow
along easily. The notes will be made available as a PDF in the
description below.

Data Structures and Algorithms
Data structures are used to arrange data in main memory for
efficient usage while algorithms are a sequence of steps to
solve a given problem. In this course, we will cover arrays,
linked lists, and graphs as examples of data structures and
dive into solving problems using different algorithms.

Programming Languages
C and C++ will be the primary languages used in this course
but Java can also be used to implement the algorithms. I do not
recommend Python or JavaScript for beginners but rather
suggest learning C to get a solid foundation in programming.

Conclusion
Learning data structures and algorithms is a responsibility and
I will teach this course in a way that is easy to understand for
beginners. Don't worry if you make mistakes or have trouble at
first, just follow along step by step and everything will become
clear.

,DATA STRUCTURE AND ALGORITHM
#LECTURE 1



Time Complexity and Big O Notation (with
notes)
CodeWithHarry
I have a story to share with you all. One day, I was feeling
extremely bored at home, and nothing seemed to interest me. I
decided to call up my friend who lives 5km away from me. Let's
refer to my friend as X.

Shubham, okay. And this friend lives 5km away. Listen
carefully. Now, what happened was, I was feeling really bored
and needed some entertainment. This guy has amazing games
like PUBG and GTA5. He has a collection of games and enjoys
playing them a lot. You can get every type of game from him,
but there is one problem:

 He lives 5km away
I also use Jio. He also uses Jio. What does he use? He also uses
Jio. We get 1Gb. We get just 1 Gb for one day. And we are not
much into broadband internet. And with more internet, we
can't sell files and all. So if I have to take the game from him,
So for me

Fastest Way to Obtain a Game
If you are looking to obtain a game quickly, perhaps from a
friend, there are a few options to consider:

 Ask your friend to share the game with you digitally
 Borrow the physical copy of the game from your friend
 Purchase the game online for immediate download
Ultimately, the choice will depend on your friend's willingness
to share or lend the game, as well as your own preference for
digital or physical copies.

Copy the hard disk and transport it. To accomplish this, I will
use my bike.

I am currently going through my bike. I plan to retrieve a game
and indulge in it to satisfy my soul. However, you may be
wondering why I am telling you this story. I simply want to

,DATA STRUCTURE AND ALGORITHM
#LECTURE 1

inquire whether it is worth it for me to retrieve a game that is
only 250kb in size. Do I really need to go to the owner's house
and bring it back on a hard disk? Please let me know.

Asymptotic Notations: Big O, Big Omega
and Big Theta Explained (With Notes)
CodeWithHarry
When comparing two sorting algorithms for an array, it can be
difficult to determine which is better and by how much. In this
video, we will discuss asymptotic notation and how it can help
us evaluate the efficiency of different algorithms.

If you have not already accessed the Data Structures
Algorithms playlist, be sure to check it out in the description
for all the necessary materials, including PDF notes for this
video and previous and future videos.

Asymptotic Notations
If you want to compare algorithms, you need to use asymptotic
notations. There are three primary types of asymptotic
notation:

 Big O
 Big Theta (Θ)
 Big Omega (Ω)
Let's take a closer look at the differences between these three
types.

Understanding notations like big O, omega, and theta becomes
crucial when it comes to exams or interviews. However, I'll
simplify these concepts for you in easy language. By the end of
this video, you'll have a clear understanding of these three
notations.

Let's start with big O. It's represented by the capital letter O
and refers to the upper bound of an algorithm's time
complexity. In other words, big O notation tells us the
maximum amount of time an algorithm will take to complete.

, DATA STRUCTURE AND ALGORITHM
#LECTURE 1

In English, we have the concept of Big O notation. Essentially,
Big O describes the relationship between two functions: f(n)
and g(n). We say that f(n) is O(g(n)) if there exists a constant c
and a constant n such that 0 ≤ f(n) ≤ cg(n).

To better understand this definition, let's try visualizing it.
Imagine a graph with function f(n) on the y-axis and n on the x-
axis. The graph of f(n) should be below or equal to the graph of
cg(n). This is what we mean when we say f(n) is O(g(n)).

When discussing a function, it is important to understand the
concept of big O notation. A function f(n) is said to be O(g(n)) if
there exist a pair of constants (c) and (n0) where the following
condition applies:

 n ≥ n0
 0 ≤ f(n) ≤ cg(n)
Essentially, this means that the growth rate of f(n) is no
greater than the growth rate of g(n). It is important to
understand this concept when analyzing algorithms and their
efficiency.

A constant n-node is defined as follows:

 0 ≤ f(n) ≤ cg(n)
This definition can be found in the notes and should not cause
any issues.

Best Case, Worst Case and Average Case
Analysis of an Algorithm (With Notes)
CodeWithHarry
Have you ever experienced a moment in your daily life where
something really good happens to you? It could be anything
from getting a promotion at work to finding money on the
street.

Study Hack: