Original subtitles

Hello, everyone, and welcome back.

So in this video, I want to do a quick walkthrough of the curriculum and talk about what to expect

from discourse.

Discourse calls explain the concept from basic to advanced so it's advisable not to miss N.S. before

you go to the next section.

The very first section is introductory section in which I explain basic content, such as what is data

structure, what is algorithm and why we need them.

Then the next section is called recursion, which is really important stuff.

So this is used in many algorithms.

So it's very important to learn before diving into the deep data structures and algorithms because it

comes up later on in many of our algorithms and there are lots of interview questions about recursion

and main ones are explained in cracking recursion into requestion sections, which is our next section.

Then the next topic is big annotation.

It is a way of describing or talking about the performance of efficiency, of course.

So we use this section all the time.

So definitely do not skip that.

And there are many different questions that are convoluted to be.

So the most asked questions are explained here in the section of cracking because Intervale questions.

Then we move on to the next section called Eris, in which we explain different types of areas such

as one dimensional array, two dimensional arrays.

And we have introduced have the arrow presented in memory and we have calculated time and space complex

for area operations.

The next we should all to talk about Python list, which is very similar to the arrays, just a small

difference.

So we explain the differences between them.

Then we analyze the interview questions related to arrays and python these.

Then from here, we continue to explain built data structures of Pathum, which are dictionaries and

tables, and we have analyzed these data structures by using people annotation to calculate the performance,

then we continue to the longer section of discourse, which is called Link.

At least here we have culled all details of Link, at least with performing all operations on different

types of Lincoln list, such as single link, at least subclassing.

The link, at least double link at least, and circler double the link.

At least you'll never find such detailed information on any other course on the Internet about Nicolelis.

Additionally, we have explained famous interview questions about Nicolelis in a separate section.

Then we move on to do two more additional data structures which are stacks and choose.

And these are very commonly used data structures.

And here also common interview questions are explained about them.

Then from here, we start another very detailed section which describes how all three data structures

in which we include Binary three and the main concepts of binary three, such as preorder traversal

in order traversal posto the traversal and Lerro to travel.

So here again we recall things like bingo, annotation and recursion.

Then from here we continue to do minor surgery.

And then absolutely, in April three, we have covered important concepts like left, left condition,

left, right condition, right, right condition and right left condition.

And we have implemented these conditions in inserting or deleting AMOLED in a Belltrees decision section,

in my opinion, because there are a lot of challenging problems that we are doing over here, then we

are going to the binary heap, which is related to trees, but a very special case of tree.

And we talk about common operations of binary.

And finally we go to the last type of tree, which is try the try to extractors as a not.

So it is very useful, especially with the blubbing applications like dictionaries.

Then from here we go to the hashing section.

So here we talk about a very particular data structure, which is very interesting.

So here we explain how Python built in data structures work and how they are implemented behind the

scenes.

And how would you implement a key value pair data structure by yourself.

So from here we get to the sort of second part of the course.

Up until this point, we have been talking about different types of data structures.

But from this section, we will start to talk about different types of algorithm.

So from this slide to the end, of course, we'll talk about different types of algorithms, which are

very essential concept of computer science.

So we move on to the sorting algorithms in which we will learn several different sorting algorithms.

We start with Barbasol, which is often considered the easiest one, and we move on to the selection

sort and then we move to the insertion zone and those three form a little group of intermediate or elementary

sorting algorithms.

Then we move to the back and sort, then merge sort and then quicksort and the sorting algorithms all

involve recursion and B1 notation.

That's why it's very important not to skip those lectures before you come over here.

Then we finish up this section with Ketso.

Then from here we go to the another detail section, which is called Graph Algorithms, something that

a lot of people are intimidated by.

So here first we start to explain graph data structures and show how to implement them using Python.

Then we continue to the implement graph algorithms like for search that first search which are used

in graph terrorism.

Then we continue to find topological support for a given graph.

Then from here, we will continue to solve problems like single source for spot problem and all patients

path.

Problem solving will solve these problems using four different algorithms such as breathless search,

Dijkstra's algorithm, Bellmon for algorithm and Photoshop.

And we'll also talk about why we cannot use that first search algorithm for these problems over here.

Then from here we will continue to the minimal spanning three, which is a special type of graph, and

we will solve this problem using two different algorithms likes primes algorithm and Kruskal algorithms.

Then this will conclude the graph section and we move onto the next section, which is called Grid Algorithms.

So here we talk about which algorithms use Ritterbusch and we solve problems like activity, selection,

problem, quoin change problem and fractional method problem using Grealy approach.

Then the next section is divide and conquer algorithms.

Here I will talk about main properties of divide and conquer algorithms and we could learn how can I?

Identify and solve problems using divide and conquer approach.

Then we'll solve problems like no fatto problem house, no problem.

There's one string to another string.

Zero, an knapsack problem, longest common, subsequent problem, longest palindromic subsequence or

substring problem, minimum cost problem using divide and conquer approach and will create methods in

Python for those problems over here and from here will continue another detail section, which is called

a dynamic program.

I know many people are curious about learning dynamic programming.

So here I will talk about main properties of dynamic programming such as optimal substructure property

and overlapping solve problems property.

Then they will learn to matters of dynamic programming, which are top down lead memorization and bottom

up with tabulation.

And also you force them to convert, divide and conquer algorithm to a dynamic algorithm.

Then you continue to learn common problems that can be solved using dynamic programming such as no factor

problem.

How severe a problem convert one string to another string problem zero.

An upset problem using dynamic programming.

So after this action, I have created a challenging dynamic programming exercise, etc. for those who

like pain and misery because these are quite hard problems.

So if you are interested to solve heart problems in the name of programming, you can continue with

this section over here.

Then finally, we will reach the Wild West section, which includes coding exercises for all topics

that we have explained in this course.

So that is where we finish this course.

But this is not the end because I'm in process of recording new sections based on your requirements

and more sections are about to come.

So hopefully you will enjoy the course.

So see you in the course.