Who is this course for?
The course aims to provide an introduction to theory and methods from data mining and knowledge discovery. It is intended for people with a background in Computer Science who have studied machine learning (ML) and artificial intelligence (AI).
What will you learn from this course?
Students will learn about the data mining pipeline, which includes data collection, cleaning, processing, analysis, and knowledge discovery. The course further discusses some ML techniques useful for data mining, such as association pattern mining, clustering analysis, and outlier analysis.
What is the format for this course?
Instruction type: Lectures are delivered via a video conference tool and in English. In addition to the lectures’s slides, a few complementary materials as a Jupyter notebooks, will be provided, allowing the participants to dig into the concepts presented in the lecture and put them into practice.
Frequency: The course is broken down into six lectures and few lab sessions presented biweekly over two months.
Examination: The students will demonstrate their knowledge in completing one assignment and a final project.
Email: shahrooz.abghari [AT] bth [DOT] se