Data Mining

Data Mining, available at $44.99, has an average rating of 4.2, with 58 lectures, 7 quizzes, based on 94 reviews, and has 663 subscribers.

You will learn about Be introduced to data mining, its advantages and disadvantages. Be aware of the importance of visualizing data. Know the usefulness of data mining in different businesses. Look forward to applying data mining to their businesses. This course is ideal for individuals who are IT managers looking to improve data management and analysis techniques. or Data analysts investigating the processes and tools of successful Data Mining. It is particularly useful for IT managers looking to improve data management and analysis techniques. or Data analysts investigating the processes and tools of successful Data Mining.

Enroll now: Data Mining

Summary

Title: Data Mining

Price: $44.99

Average Rating: 4.2

Number of Lectures: 58

Number of Quizzes: 7

Number of Published Lectures: 48

Number of Curriculum Items: 65

Number of Published Curriculum Objects: 48

Original Price: $39.99

Quality Status: approved

Status: Live

What You Will Learn

Be introduced to data mining, its advantages and disadvantages.

Be aware of the importance of visualizing data.

Know the usefulness of data mining in different businesses.

Look forward to applying data mining to their businesses.

Who Should Attend

IT managers looking to improve data management and analysis techniques.

Data analysts investigating the processes and tools of successful Data Mining.

Target Audiences

IT managers looking to improve data management and analysis techniques.

Data analysts investigating the processes and tools of successful Data Mining.

Uncover the essential tool for information management professionals known as Data Mining.

Data mining is the process of extracting patterns from large data sets by connecting methods from statistics and artificial intelligence with database management. Although a relatively young and interdisciplinary field of computer science, data mining involves analysis of large masses of data and conversion into useful information.

This introductory course will discuss: its involvement in the 9-step KDD process, which data can be mined and used to enhance businesses, data patterns which can be visualized to understand the data better, the process, tools, and its future by modern standards. It will also talk about the increasing importance of transforming unprecedented quantities of digital data into business intelligence giving users an informational advantage.

Course Curriculum

Chapter 1: Introduction to Knowledge Discovery in Databases

Lecture 1: Introduction and Objectives

Lecture 2: Definition of Knowledge Discovery in Databases

Lecture 3: Techniques in Knowledge Discovery in Databases

Lecture 4: Process in Knowledge Discovery in Databases

Chapter 2: Introduction to Data Mining

Lecture 1: Introduction and Objectives

Lecture 2: Definition of Data Mining

Lecture 3: Styles of Learning

Lecture 4: Advantages in Data Mining

Lecture 5: Disadvantages in Data Mining

Lecture 6: Data

Lecture 7: Information and Knowledge

Lecture 8: Data Warehouses

Lecture 9: Decision Tree Learning

Chapter 3: Minable Data

Lecture 1: Introduction and Objectives

Lecture 2: Types of Data Studied in Data Mining

Lecture 3: Minable Information

Chapter 4: Visualizing Data Patterns

Lecture 1: Introduction and Objectives

Lecture 2: Introduction to Visualizing Data Patterns

Lecture 3: Orienteering

Lecture 4: Why Visualize?

Lecture 5: Trusting a Model

Lecture 6: Understanding a Model

Chapter 5: Data Mining Process

Lecture 1: Introduction and Objectives

Lecture 2: What Can Data Mining Do?

Lecture 3: Types of Data Sets

Lecture 4: Data Mining Process

Lecture 5: Process Flow

Lecture 6: Conclusion

Chapter 6: Data Mining Tools

Lecture 1: Introduction and Objectives

Lecture 2: Introduction to Tools

Lecture 3: Data Mining Tools

Lecture 4: Data Mining Techniques

Chapter 7: Usefulness and Future of Data Mining

Lecture 1: Introduction and Objectives

Lecture 2: Usefulness of Data Mining

Lecture 3: Basket Analysis

Lecture 4: Sales Forecasting

Lecture 5: Database Marketing

Lecture 6: Merchandise Planning

Lecture 7: Card Marketing

Lecture 8: Call Detail Record Analysis

Lecture 9: Customer Loyalty

Lecture 10: Marketing Segmentation

Lecture 11: Product Production

Lecture 12: Warranties

Lecture 13: Future of Data Mining

Chapter 8: Course Resources

Lecture 1: Data Mining Glossary of Terms

Chapter 9: Data Mining Certification

Lecture 1: Final Exam

Lecture 2: Conclusion – Final Lecture

Instructors

The Art Of Service
Quality education for Career Driven IT Professionals

Rating Distribution

1 stars: 13 votes

2 stars: 10 votes

3 stars: 18 votes

4 stars: 29 votes

5 stars: 24 votes

Frequently Asked Questions

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