Computer Science, Second Cycle, Data Mining, 3 Credits

Data mining is essential for uncovering valuable insights in large datasets. While many companies focus on AI and deep learning, the real challenge is understanding and preparing data before building advanced models. Defining the right problem and extracting meaningful patterns are key steps in making data-driven decisions.

The data mining course covers practical techniques for working with data, from preprocessing, visualization, and statistical analysis to pattern recognition methods like association rule mining, anomaly detection, and clustering. Through hands-on programming assignments and real-world examples, participants will gain the skills to explore data effectively and support decision-making in their organizations.

This course is intended for working professionals.

ECTS Credits

3 Credits

Level of education

Second cycle, has only first-cycle course/s as entry requirements (A1N)

School

School of Science and Technology