This course introduces students to Data Mining technology, examines in detail the methods, tools, and application of Data Mining. A description of each method is accompanied by a specific example of its use.

The differences between Data Mining and classical statistical methods of analysis and OLAP systems are discussed, and the types of patterns revealed by Data Mining (association, classification, sequence, clustering, forecasting) are examined.

The scope of Data Mining is described. The concept of Web mining is introduced. The Data Mining methods are considered in detail: neural networks, decision trees, limited enumeration methods, genetic algorithms, evolutionary programming, cluster models, combined methods. Familiarity with each method is illustrated by solving a practical problem with the help of instrumental.

Tools that use Data Mining technology.

The basic concepts of data warehouses and the place of Data Mining in their architecture are described. The concepts of OLTP, OLAP, ROLAP, MOLAP, Orange software are introduced.

The process of data analysis using Data Mining technology is discussed. The stages of this process are considered in detail. The analyzed market of analytical software describes products from leading Data Mining manufacturers, discussing their capabilities.

Purpose To acquaint students with the theoretical aspects of Data Mining technology, methods, the possibility of their application, to give practical skills in using the Data Mining tools.

Prior knowledge

Knowledge of computer science, the basics of database theory, knowledge of mathematics (within the initial courses of a university), and information processing technology is desirable, but not required.

By John Morris

John Morris is an experienced writer and editor, specializing in AI, machine learning, and science education. He is the Editor-in-Chief at Vproexpert, a reputable site dedicated to these topics. Morris has over five years of experience in the field and is recognized for his expertise in content strategy. You can reach him at [email protected].

One thought on “Data Mining basics”
  1. Thank you for sharing your info. I truly appreciate your efforts and I will be waiting for your further
    write ups thanks once again.

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