Data Analytics

This course covers foundational concepts in the analysis of data to help gain insights from complex datasets, using the Python programming language to demonstrate and put into practice said concepts.

The main topics of study are:

1. Design of data-centric studies.

2. Exploratory data analysis.

3. Data modeling.

4. Regression.

5. Classification.

6. Clustering.

7. Dimensionality reduction.

8. Data analysis with Python.

Two parts:

- Written exam with multiple choice questions and open-ended questions (70%)

- Lab assignments (30%).

In order to pass, students must obtain a grade greater or equal to 5.8 in each part.

Repairs are only possible for parts with a fail grade (passing grades are kept for the resit).

Information may change depending on unforeseen circumstances or measures (see: TER Art 29, sub 4)