Description and contextualization of the subject

This short course aims to give the students a meaningful introduction and hands-on experience of what data science is, to teach them how to continue to learn data science, and to give them the desire and skills needed to do so. The provided materials will perform as an index. For each topic, the aim is to give a cursory overview and a simple demonstration of what the topic under investigation is, and guide the students to bigger and better resources to really dive into it.

Learning outcomes of the subject

Competencies:

RC3 - Being able to think statistically and conduct data-driven research.



Abilities or skills:

RHE1 - Being able to think analytically.

RHE3 - Being able to write technical documents and reports.

RHT5 - Being able to perform data analysis and visualization in a expressive and meaningful way.

RHT6 - Being able to apply Machine Learning techniques to estimate models relating different variables and magnitudes.

Temary

1- Overview

2- Computing with Python

3- Data collection, transformation, exploration and visualization

4- Machine learning for data modeling

Bibliography

Compulsory materials

- Apuntes de la asignatura