It is step by step learning of DSA . This course covers all points from very basic to advance . we cover all the key tools and key points in this DSA notes like data , data structures , types of data structures , Algorithms , stack, queuing models etc. we tried to put all the important knowledge i...
should be able to use it in your work or in your projects or in your courses or in your projects that
you are doing in the future or in your work that you are doing right now so if you want to use
something then you should be able to use it in your work or in your projects or in your courses or
in your future work or in your projects that you are doing right now . So data structures and
algorithms are things that help us in our work or in our projects or in our courses or in our future
projects or in our work or in our projects that we are doing right now so if you want to use
something then you should be able to use it in your work or in your projects or in your courses or
in your future work or in your projects that you are doing right nowwater in a pot and you put the
tea bag in the cup and you make the coffee Now what is the difference between data structures
and algorithms? Algorithms are specific steps that need to be taken in order to solve a
problem.I have been in the industry for a long time now and I have seen a lot of people learning
C , C++ and when they start to learn it they get very lost & confused & they don't know what they
are doing & they don't know how to use the language properly & eventually they stop learning it
& they end up becoming a beginner again & that is not good for the industry & it is not good for
the learners either so I would say learn C , C++ & don't get lost in the language learning process
a break for a while I understand that you are very busy for the next few days and I understand
that you are very busy for the next few weeks and I understand that you have a lot of questions
so I 'll just stop now and I 'll come back to you in a few days and we will start the next lecture
where we will talk about algorithms and data structures and then we will talk about interviews
and then finally we will talk about the final exam and you can ask me any questions that you
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,have in your mind so that 's all for now I 'll come back to you in a few days and we will start the
next lecturewhat is the data structure of chrome so now we see that the data structure is called
RAM so the data structure of a database is called RAM because when the program starts it will
load into RAM the data structure of the database which is called RAM . And then you will get to
hear this and it is asked in the interviews, "tell me, what is this?" So now let's understand
database, data warehouse, and big data here we have understood the data structure that when
your program starts in RAM, it will load into the random access memory.I want to keep the data
in a different database so what I have to do is I have to create a new database and I have to
name it `` legacyData '' I have to create a new table in that database and I have to add the
following column in the table `` Birthday `` I have to add the following column in the table `` Year
`` Now I have to run the program and I will get the following result in the console `` Facebook
2020 `` Facebook 2021 `` Facebook 2009 `` `` Facebook 2020 `` Facebook 2021 `` Facebook
2009 `` `` Facebook 2009 `` You retrieve and read the data from hard disk drive and update it.
know these three terms because big data is what we are talking about here .memory location
where the C program stores the data that is to be processed next and the heap is a memory
location where the C program stores the data that is to be processed next but the data that is to
be processed next is not always stored in the same location as the data that is to be processed
next because the C program can keep data in different memory locations depending on the
situation and this is why it is important for you to understand the stack and heap because you
will be able to understand the C program better and be able to ask more questions on the C
program. Alright ... I 'm talking about C program that 's why I say that you get a good picture of
memory with the help of C programming therefore , data structures and algorithms is best
learned from C and C++ Now here I am dividing it into segments so there is thing called code
segment let 's say this is our code let 's say there is a code with the name `` harry.c '' now this
code will be first loaded into our main memory I told you what is the first thing that happens ?
then it will come to this line it will come to fun1 ( ) , it will execute fun1 ( ) . fun2 ( ) is calling
inside fun1 ( ) now the variables that I had created inside it will be created here let 's say I have
created `` k '' & `` l '' let me write here : initialize k and l and after that I 'm calling fun2 ( ) so as
soon as fun2 ( ) will be called it will say to fun1 ( ) that you wait for a while , I call fun2 ( ) and be
back by fetching the value whatever it will return fun1 ( ) replied that you go and get it call fun2
( ) and get its value .
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,me where do I give the milk to the milkman because the pointer will store the address of the
malloced memory so the milkman will get the milk from the pointer and the pointer will stay
there until you return the function or until you delete it.it will say to fun1 ( ) that you 're coming
back and now you can start your execution again . If anyone asks you this question, that why
heap is used, it can also be done from stack. So that thing is done here with the help of dynamic
memory because when does the stack of a function end it ends when the function is returned. I
just come back with the value you just wait here. You go and get it and then what will happen,
fun function will be called.
this lecture we will focus on linked list & binary search tree so if you want to know more about
these then you should go ahead and watch the lecture and learn more about these things . If you
still think that you want to do all of these things with Python, then I am saying that when you will
go for an interview, the person in front of you will expect C, C++, or Java from you.
Time Complexity and Big O Notation (with notes)
So the input size didn't increase and the runtime of the algorithms didn't increase either .No , it
doesn't depend on the size of the input . When we ask questions like as the input will increase,
Then the runtime will change as per what? And after that Now you will go to aunty's house You
will be treated. Consider there are different routes to come and go.
is the algorithm that runs in constant time . K1 n to the power 0+k2+k3+k4 This time is required
in algo 2 .The sentence is: Run time of it, there are some things that we will recite. Because we
won't constantly use our brains again and again, as we see Big O of 1 it is constant. Now, come
here and listen to another story. If we do an analysis of the first algorithm, If I do T algo1 Then
what will happen here? And along with consider that game is of L3 kb. If the game is of N kb
then how much time will you need? The sentence is: Run time of it, there are some things that
we will recite.There are polynomial algorithms and there are exponential algorithms and there
are logarithmic algorithms and there are exponential functions and there are logarithmic
functions. There are also algorithms that are not linear in time.
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, Asymptotic Notations: Big O, Big Omega and Big Theta
Explained (With Notes)
We 'll talk a little bit about asymptotic notation. we talked about order. We talked about ordering.
We have primarily 3 types of asymptic notation big O, big Theta (Θ ) and big Omega (Ω) big O is
represented by capital (O), which is in our English. Big O is set to be O ( g ( n ) ) if and only if there
exist a constant ( c ) and a constant n -node such that 0 ≤ f ( n) ≤ cg (n) is O (g (N) If you watch this
lecture completely then I guarantee that you will understand these three notations. Mathematically,
mathematically this function can be anything. When we do analysis of algorithms comparing any 2
algorithms then f ( n ) will be time and what is n , it 's input ok , size of input. G ( n) is your function
which will come inside the big O. O ( n²) is Anything Can Be Algorithm it is g (n) that will be here
and which is your algorithm. If you guys can find any such constant ( C ) and ( n ) -node , then f ( n)
is O ( g ( n)" This is the mathematical definition of big O. If you ca n't find it then its is not f (n ) is
O. This question is its own truth , it has validity , it will remain valid.
Best Case, Worst Case and Average Case Analysis of an
Algorithm (With Notes)
To define an algorithm, To define the events in the life of an algorithm , We have , Best Case
Worst Case and Expected Case. And along with that, I 've packed one more thing into this
lecture : The definition of Log. If you watch this lecture till the end , Then you will find out what
this 'Log ' really is. 1. . . 5. . . 7. . . 9 and 24 are the numbers in it; They 're in ascending order , You
can see for yourself. If you know even a bit of maths, You 'll know that it is in an ascending
order. Now what I say is that I 'll give a number : 'A' And I 'd like you to tell me If this number
exists within the array , or not. Suppose the value of A is 8. So what will be your answer ? Yes.
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