Data Mining Course And Certification

What is Data Mining? 

Data Mining is the process of extracting usable data from a large set of any raw data. Data mining is a key part of knowledge discovery that helps to analyse an enormous set of data.

Data Mining can also be defined as the process of sorting through large data sets in order to discover and identify patterns and establish relationship through data analysis. 

Advantages of Data Mining:  

1. Data Mining helps to extract information from a data set to give a meaningful insight for better decision making. 

2. Data Mining helps in association/correlation between products sales. 

3. Data Mining helps in checking competitors and monitoring market directions. 

4. Data Mining helps in checking resources and spending. 

5. Data Mining helps in checking and identifying criminality. 

6. Data Mining helps to identify the kind of products your customers prefer per time.

7. Data Mining offers accurate market analysis.

8. Data Mining helps in fraud detection.

9. Data Mining helps in customer retention.

10. Data Mining helps in science exploration and research.

11. Data Mining helps in gaining higher returns on investment.

12. Data Mining provides job opportunity.

Features of Data Mining:

1. Data Mining implies analysis of data patterns in large batches of data using one or more softwares.

2. Data Mining has application in multiple fields such as fields like science and research.

3. With Data Mining, businesses can get more information about their customers and develop more effective ways to improve business functions.

4. Data Mining is used in effective data collection and warehousing as well as computer processing for arrangement and evaluation of the data.

5. Data Mining uses sophisticated mathematical algorithm.

6. Data Mining is also known as knowledge discovery.

7. Data Mining is a process used by companies to turn raw data into useful information.

8. With Data Mining, businesses can learn more about their customers to develop more effective marketing strategies, increase sales and decrease costs leading to higher profitability.

9. Data mining depends on effective data collection, warehousing, and computer processing.

10. Data mining can be used in a variety of ways, such as database marketing, credit risk management, fraud detection, Spam email filtering even to discern the sentiment or opinion of users.

The Data Mining Process: 

The Data Mining process are broken down into these five steps: 

1. Organizations engage in collection of data and load it into their data warehouses. 

2. Organizations stores and manage the data, either in-house-server or on the cloud.

3. Business analysts, management teams and information technology professionals access the data and determine how they want to organize it for use. 

4. Applications software sorts the data based on the user's results. 

5. Lastly, the end user represents the data in an easy to share format such as in graphs or tables.

In the Full Course, you will learn everything you need to know about Data Mining with Certification to showcase your knowledge/skill gained.

Data Mining Course Outline: 

Data Mining - Introduction/Overview

Data Mining - Tasks

Data Mining - Issues

Data Mining - Evaluation

Data Mining - Terminologies

Data Mining - Knowledge Discovery

Data Mining - Systems

Data Mining - Query Language

Data Mining - Classification & Prediction

Data Mining - Decision Tree Induction

Data Mining - Bayesian Classification

Data Mining - Rules Based Classification

Data Mining - Classification Methods

Data Mining - Cluster Analysis

Data Mining - Mining Text Data

Data Mining - Mining WWW

Data Mining - Applications & Trends

Data Mining - Themes

Data Mining - Exams and Certification

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