The first half of this course introduces classical data mining problems and algorithms. The second half examines a range of data types commonly encountered in practice and the corresponding mining tasks.
Assignments combine analytical exercises with Python programming tasks to build students’ core problem-solving and implementation skills. For the final project, students work in teams to select a real-world problem from Kaggle, apply techniques learned in class, and present their methods and results in a clear, well-structured report.