Data Mining II

The aim of the course Data mining is to acquaint students with the processes and methods of implementation of research and analytical tasks of data science, principles, methods, and procedures of using big data management. The teaching is focused mainly on the preparation and modification of databases and the subsequent use of data mining tools. The student has knowledge related to the transformation of data and information into appropriate data models, structures, or architectures. Can prepare proposals and argue them regarding the optimal structure for a specific domain, industry, sector.
As part of their professional skills, they will gain an overview of the use of data mining software: R, Python, Orange, Weka. The graduate is able to perform data analysis activities, especially steps related to pre-processing - cleaning, consolidation, aggregation, organization, is able to work on creating a data model, it's learning, or improvement in the context of data. Thanks to the teaching methods used, graduates will improve their competencies in the field of independent presentation. They will deepen critical thinking through an objective analysis of the problem and especially by examining the problems from different angles and perspectives. Graduates will learn to approach problems by identifying existing assumptions and resources, they will learn to think creatively and look for context in a deeper context.