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