OPCO 2115 - Introduction to data science for public policy

The goal of this course is to equip students with technical tools and methodologies to analyse data. You will learn to manipulate and analyse real datasets of interest for public policies (e.g. housing prices in Paris) in order to make data-driven decisions. You will be introduced to basic statistical concepts, as well as software and programming frameworks to apply them. By the end of the 12 classes, you will be able to identify situations where data can be leveraged to orient public policy.

No prerequisite, except eagerness to learn hard skills

A typical class takes place on site, with

10 min. review of previous courses’ key concepts

20 min. presentation of a new concept

30-60 min of practice (essentially coding)

Groups of 3-4 students will work on two to three assignments, which will be related to a public policy issue and include a dataset. Students will be expected to analyse the data and produce a report including key takeaways. The format can be written or verbal (presentation).

Additionally, participation will count for 10% of the total grade.

Consistent practice is required to master the data science tools:

We recommend 30-60 minutes between each session to review concepts and practice coding

Expect 4 to 8 hours to complete assignments