Currently pursuing B.Tech in the field of computer science. Exploring the world of Artificial Intelligence

Palash Sharma

In this course, Palash Sharma will cover the introduction to Data Mining and Warehousing and along with this, also will be discussing the details related to it

GATE (Graduate Aptitude Test in Engineering) 2020 & 2021 complete preparation with best educators. Know about the detailed syllabus, best books, exam pattern and dates, previous year question papers a

GATE - Iconic Pro

English

Data Mining And Warehousing: GATE

Greedy Techniques

Algorithms

CS & IT

GATE - CSIT, DSAI & Interview Preparation

GATE, ESE and IIT-JAM

Ace the toughest competitive and government exams in India 

Test Preparation

In this lesson, we look at the introduction to Data Mining and the techniques and methods how it is performed.

Introduction to Data Mining

Let's have a look at the introduction to Data Warehousing and how it is helping the companies in decision making process.

Introduction to Data Warehousing

Let's have a look at how Data is preprocessed for Data Mining and warehousing processes and understand the techniques for their implementation.

Pre-Processing Techniques

Here we will learn about the Data Warehousing Modelling and the different Schemas which are used for building it.

Data Warehousing Modelling

It's time to learn about OLAP Operations and how they help in preprocessing and other aggregation techniques used for Data Mining and Warehousing.

OLAP Operations

Let's dig deep in Data Mining and learn about Classification and its techniques like Decision tree and Bayesian Classification. Also,  understand about confusion matrix.

Introduction to Classification and Basic Techniques

It's time to learn about Backpropagation method and Support Vector Machine which are used as Advanced Classification methods in Data mining.

Advanced Classification Methods

Let's see how Clustering and its techniques can help us in Data mining and analysis of various data sets.

Introduction to Clustering and its Techniques

Let's understand about Outlier Detection and the ways in which it is performed by looking at various techniques.

Introduction to Outlier Detection

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 discuss Graph Algorithms in detail with concepts first and then previous year questions on this topic. So, this is a complete course in Graph Algorithms that have a Weightage of 2 marks.

(Hindi) Graph Algorithms Concepts and PYQs : GATE (CS/IT)

This course will cover Shortest Path Algorithms like Djikstra, Bellman-Ford and Floyd Warshall Algorithm. The course will be beneficial for GATE Aspirants.

(Hindi) Shortest Path Algorithms Practice Questions: GATE (CS and IT)

This course will cover Algorithm Designing Approaches With Problems and thier Solutions.

(Hindi) Greedy Algorithm Designing Approaches - GATE (CS & IT)

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

Sourav Newatia

Divide and conquer is an algorithm design paradigm based on multi-branched recursion. In this course, the educator will cover all the D & C methods like linear search, Binary search, Merge sort, Quick sort, Matrix multiplication, Integer multiplication, Min-Max Algorithm, set Algorithms, Tree representation, Priority Queue, and Heap.

Divide and Conquer Methods: GATE (CS and IT)

 Btech in CSE and  Mtech in Intelligent Systems and Robotics . GATE Qualified. Currently working as an associate Software Developer at Globa

Akansha Aggarwal

This course discusses searching algorithms and hashing and its different collision resolution techniques with previous year gate questions

Searching and Hashing for GATE

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

Lessons

9 lessons • 1h 49m

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Introduction to Data Mining

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Introduction to Data Warehousing

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Pre-Processing Techniques

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Data Warehousing Modelling

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OLAP Operations

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Introduction to Classification and Basic Techniques

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Advanced Classification Methods

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Introduction to Clustering and its Techniques

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Introduction to Outlier Detection