This course introduces students to the world of data analytics and visualization, emphasizing its essential role in data analysis and decision support within organizations. Students will learn how to present data in a clear, comprehensible, and visually engaging way to effectively communicate key insights.
The course covers the theoretical foundations of data visualization, including cognitive aspects of perception, the use of color and symbols, and the interpretation of complex data patterns. Students will explore various types of visualizations, techniques for presenting large datasets, data storytelling using graphs, and the application of descriptive statistics to enhance data understanding.
In addition, the course introduces key data mining concepts as a core component of data analytics. Students will learn fundamental techniques such as clustering, classification, association rule mining, and anomaly detection. Emphasis will be placed on how these techniques uncover hidden patterns, relationships, and trends in large datasets, which can then be translated into meaningful visual representations.
- Učitel: Adam Karol Czerniak
- Učitel: Jakub Fischer
- Učitel: Tereza Krajíčková
- Učitel: Kristýna Vltavská