Data mining is the discovery of patterns and hidden information in large data sets. This course provides you with the details about most aspects of data mining with focus on techniques and algorithms, and their applications in business. The course also provides you with details in model building and interpreting and validating results.
You will learn from:
- Hands-on experience with algorithms used for data-mining
- Easy-to-use software Rapid-miner for analysis
- Real cases
The goal of the data mining course is that the participant should have gained a solid understanding of the basic data mining concepts and techniques and how they are used in a business context.
Active study of real cases between blocks
- The concepts of data mining, its motivation, definition, the relationships of data mining with database systems, statistics, machine learning and information retrieval.
- Understanding and analyzing the knowledge discovery process with emphasis on the iterative and interactive nature of the KDD process.
- Mine different kinds of data: relational, transactional, object-relational, spatiotemporal, text, web.
- Mine for different kind of knowledge like classification, regression, clustering, frequent patterns, discriminant, outliers etc.
- Evaluate knowledge: interestingness or quality of knowledge, including accuracy, utility and relevance.
- Data mining applications: market basket analysis, energy, insurance, sports and health.
- Model and solve data mining problems with Rapid Miner [member of Gartner’s magic data quadrant, 2015].