Description: This course will provide students with an in-depth understanding of data science-both how to cope with complex data structures and how analysts make use of it to test theory, speak to policymakers, and find facts. This course is intended to master students and is the first approach to coding in python.

• Course material: https://github.com/andreaguido/datasciencewithpython

• Book: "Python Data Science Handbook"

Description: The aim of this subject is to provide economists sufficient knowledge of the most updated topics in microeconometrics so that they can choose the most appropriate estimators as well as exploit both the databases and economic models. The program is designed to respond to the needs of researchers and practitioners when working with real data, where an important dimension in the unit of analysis is the individual. This requires the use of micro data and the use of advanced techniques in (micro) econometrics. The practical content of this course has two objectives: on the one hand, the knowledge and management of the statistic-econometric software R; on the other hand, being able to solve practical cases that require the use of the various estimators explained in the theoretical part of the program. 

• Course material: https://github.com/andreaguido/microeconometrics 

• Book: "Introductory Econometrics", Wooldridge, J.

Link to Slides