Course content

This course aims at bridging some of the gaps that are often
encountered between classical statistics or computer science curricula
and the work and research life outside academia. Students will work on
a number of real-life data sets and familiarize themselves with
relevant tools.

 

We will introduce some basics of machine learning as needed and talk
about business cases and in which industry settings one would commonly
encounter data of a given kind. Classes will be as interactive as
possible and coding exercises and project work will be offered. The
main student project will be the implementation of an applied machine
learning product, taking all considerations relevant for real-world
industry applications into account.

 

Through the course students will be introduced to modern technologies
such as cluster-computing tools (e.g. Apache Spark),  database programming
(MongoDB) and machine learning software (scikit-learn), as well as web
services and REST APIs.