(i) Gate Qualified 2016
(ii) Mtech (Cyber Security) from NIT Kurukshetra.
(iii) UGC-Net Qualified 
(iv) Cyber security analyst at Honeywell

Sourav Newatia

Asymptotic analysis of an algorithm refers to defining the mathematical boundation/framing of its run-time performance. Using asymptotic analysis, we can very well conduct the best case, average case, and worst case scenario of the algorithm.

This course states about different types of algorithms, Analysis of algorithm, Recurrence relation with example. We will also see the asymptotic notation ( Big-oh, theta, Omega) woth lots of previous year of questions.

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Asymptotic Analysis: GATE (CS and IT)

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Test Preparation

Hello friends, 

This course is all about Asymptotic notation. In this, we will cover the basic of algorithm , notation used to find the time complexity and space complexity. We will also see the difference between time complexity and space complexity. After, we will cover recurrence relation and recursive algorithm. We have see lots of previous year question , so that whatever we have read theoritical , we apply that on numerical part. All the question are once asjed in gate exam. So , that the advantage also , you will not have to find the answer. You will get all here.

Course Overview

Hello friends, 

This lesson is all about mark distribution in gate exam. So, we have seen previous 10 year mark distributon for subject Algorithm. As you will see, the average mark for algorithm is 13 marks. And the highest mark asked in gate is 25.

So, you will able to understand how important is this subject in Gate.

Mark Distribution : Algorithm

Hello friends, 

This lesson is all about Introduction of Algorithm . As you all know, Algorithm is a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer. We will also see different types of algorithm and we will start the overview about time complexity in this lesson itself.

Introduction : Algorithm (Gate)

Hello friends, 

This lesson is all about finding time complexity for different types of loops. As you all know, the time complexity is the computational complexity that describes the amount of time it takes to run an algorithm.Therefore, the time complexity is commonly expressed using big O notation, typically etc., where n is the input size in units of bits needed to represent the input. 

So we will see, the tips and tricks to solve all the different types of question related to time complexity for Gate.

Time Complexity of loop’s (GATE CS & IT)

Hello friends, 

This lesson is all about finding time complexity for different types of recurrence algorithms. As you all know, recurrence relation is an equation that recursively defines a sequence or multidimensional array of values, once one or more initial terms are given: each further term of the sequence or array is defined as a function of the preceding terms. 

So we will see, the tips and tricks to solve all the different types of question related to recursive algorithm and recurrence algorithm for Gate.

Recurrence Relation and Recursive algorithm ( Gate CS & IT )

Hello friends, 

This lesson is all about notation. After finding time complexity which notation is useful is actually we will see in this lesson.

So we will see, the three pillars of asymptotic notation (Big-Oh , Big - Omega , Theta) for Gate.

Asymptotic Notation (Gate CS and IT)

Hello friends, 

This lesson is all about notation. After finding time complexity which notation is useful is actually we will see in this lesson.As you know, Big O notation is used in Computer Science to describe the performance or complexity of an algorithm. Big O specifically describes the worst-case scenario, and can be used to describe the execution time required or the space used (e.g. in memory or on disk) by an algorithm.

So we will see, the three pillars of asymptotic notation (Big-Oh , Big - Omega , Theta) to solving different ques aksed in  Gate.

Big-O notation (Gate CS & IT)

Hello friends, 

This lesson is all about notation. After finding time complexity which notation is useful is actually we will see in this lesson.As you know, Big Omega is an algorithm takes at least a certain amount of time, without providing an upper bound. We use big-Ω notation; that's the Greek letter "omega."

So we will see, the three pillars of asymptotic notation (Big-Oh , Big - Omega , Theta) to solving different ques aksed in  Gate.

Big-Omega Notation (Gate CS & IT)

Hello friends, 

This lesson is all about notation. After finding time complexity which notation is useful is actually we will see in this lesson.As you know, Big - Theta Notation (Θ) Big - Theta notation is used to define the average bound of an algorithm in terms of Time Complexity. That means Big - Theta notation always indicates the average time required by an algorithm for all input values.

So we will see, the three pillars of asymptotic notation (Big-Oh , Big - Omega , Theta) to solving different ques aksed in  Gate.

Big-Theta Notation (Gate Cs & IT)

Hello friends, 

This lesson is all about notation. After finding time complexity which notation is useful is actually we will see in this lesson.As you know,loose upper-bound. “Little-ο” (ο()) notation is used to describe an upper-bound that cannot be tight.

So  as you see, the three pillars of asymptotic notation (Big-Oh , Big - Omega , Theta) to solving different ques aksed in  Gate.

Little-o and Little-omega Notation (Gate CS & IT)

Hello friends, 

In mathematics, a theorem that covers a variety of cases is sometimes called a master theorem.

Some theorems called master theorems in their fields include:
Master theorem (analysis of algorithms), analyzing the asymptotic behavior of divide-and-conquer algorithms

We will see the the cases that built the cases to solve differnt ques aked in gate.

Master’s Theorem (GATE CS & IT)

Hello friends, 

In mathematics, a theorem that covers a variety of cases is sometimes called a master theorem.

Some theorems called master theorems in their fields include:
Master theorem (analysis of algorithms), analyzing the asymptotic behavior of divide-and-conquer algorithms

We will see the the cases that built the cases to solve differnt ques asked in gate. In this lesson, we will see some advance method to solve masters theorem, Change of variable method and Homogenous linear equation method.

Master's Theorem part -I(Gate CS and IT)

Hello friends, 

So we have all the topic that asked in Gate exam. Now, we start from the previous year question asked in Gate . Even, we have solutions too for your help.

It will help you to clearify your doubt and solve differnt variant of various topics.

Previous Year Question - I

Previous year Question - II

Previous Year Question - III

Previous year Question - IV

Previous year Question - V

Previous year Question - VI

Previous year Question - VII

Previous Year Question - VIII

Hello friends, 

So we have all the topic that asked in Gate exam. Now, we start from the previous year question asked in Gate . Even, we have solutions too for your help.

It will help you to clearify your doubt and solve different variant of various topics.

Previous Year Question: IX

Previous year Question : X

Previous Year Question : XI

Code HELLOSONU01 | 8+ Years Teaching Exp. in GATE CS IT & GATE DS AI on Unacademy | Mentored 2 Lakh+ Students | Produced Rankers Under 500

Sweta Kumari

This course will cover Artificial Neural Networks in just 60 Minutes with full package.

(Hindi) Artificial Neural Networks in 60 Minutes

This course has discussed Sorting Algorithms with Complexities, working and some FAQs. The course will be beneficial for Engineering students and GATE aspirants.

(Hindi) Short Tricks to Remember Complexities of Sorting Algorithms

This course will cover dynamic Programming solution for Matrix Chain Multiplication and Longest Common Subsequence.

(Hindi) Dynamic Programming : MCM & LCS

This course will cover Asymptotic Analysis Of Algorithms with short notes targeted for GATE Aspirants.

(Hindi) Asymptotic Analysis Of Algorithms in 40 Minutes - GATE 2019

This course will cover Searching Algorithms Like Linear , Binary & Interpolation Search for  GATE CS/IT.

(Hindi) Searching Algorithms : Linear , Binary & Interpolation Search - GATE CS/IT

This course will cover 100 Short Tricks To Learn Complexities of Algorithms Easily. This Course is beneficial for  GATE (CS and IT) aspirants.

Lessons

23 lessons • 3h 45m

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Course Overview

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Mark Distribution : Algorithm

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Introduction : Algorithm (Gate)

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Time Complexity of loop’s (GATE CS & IT)

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Recurrence Relation and Recursive algorithm ( Gate CS & IT )

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Asymptotic Notation (Gate CS and IT)

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Big-O notation (Gate CS & IT)

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Big-Omega Notation (Gate CS & IT)

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Big-Theta Notation (Gate Cs & IT)

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Little-o and Little-omega Notation (Gate CS & IT)

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