Métodos Descritivos de Data Mining

Objetivos

The objective of the Descriptive Methods of Data Mining (DMDM) course is to introduce the students to the study of the main concepts, methods and tools available in data mining. DMDM is meant to be the first part of a two parts course, which includes Predictive Methods of Data Mining, thus it is focused on presenting the main paradigms of Data Mining (e.g. canonical tasks in Data Mining, the nature of inductive learning, the role and methods of data preparation and preprocessing) and proceeds to the explanation of the major descriptive methods usually used in Data Mining. The course does not assume familiarity of the student with Data Mining, but it is highly recommended that the students have some knowledge of inferential statistics, as well as some initial contact with Python.

The course seeks to achieve a balance between courses dedicated to in-depth analysis of the algorithms (i.e. engineering courses) and courses for managers, that seek to raise awareness about the importance of the tools. This is a technical course for all who already work or want to work in developing descriptive models and exploring big databases. As such, students will perform the activities of a typical data scientist, especially in the practical project, which constitutes a central component of the course.

The course's main challenge is presenting the algorithms in a clear and understandable manner, accessible to a wide audience with different academic backgrounds. It is intended to enable the student to understand the fundamental ideas associated with the inner workings of the different algorithms because only then the student will be able to apply them judiciously.

The course program covers the main methodological aspects as well as the most popular descriptive models. This will include visualization tools, algorithms for clustering and association rules, among others.

The course is also focused on providing the students with a hands-on experience in the application of the studied Data Mining tools in a real-world problem. The students will have the opportunity to use Python to develop the practical aspects related with the application of these concepts and tools.