Study program / study programs: INFORMATION TECHNOLOGY

Type and level of studies: Applied master’s studies

Subject: Data Science Basics

Status: elective

ECTS credits: 8


Course objective

The objective is to teach students about the principles of projecting and implementing data mining models, and train them to apply these models in a real-life environment.

Course outcome

The students have mastered the analytical process of conceptualizing, organizing, reaching, browsing and storing data (mainly big data). They can also extract information from a data set and transform it into understandable (applicable) structures, i.e. useful formats for further manipulation.

Course content

Theoretical classes

  • Methods of collecting, presenting and processing data
  • Data extraction, transformation and loading
  • Storing and managing data in multidimensional database systems
  • Software-based data analysis
  • Data attributes and relationship types
  • Data classification
  • Clustering
  • Association rules
  • Sequential patterns
  • Decision trees, inductive learning
  • Bayesian networks
  • Neural networks, genetic algorithm, instance-based learning
  • Semantic web technologies and conceptual networks, concept modeling
  • Data visualization
  • Data presentation

Practical classes

  • Exercises
  • Examples and exercises which accompany the lectures
  • Examples of specific algorithms and tools