BIO-645 / 2 crédits

Enseignant: Dayan Michaël Jérémy Pierre

Langue: Anglais

Remark: Fall 2021


Frequency

Every year

Summary

The "Introduction to Open & Reproducible Data Science" (IORDS) course is aimed at students of all levels to train them in the core computer science software stack and techniques forming the pillars of open & reproducible science.

Content

Note

The course will be made available in hybrid mode, with attendance either physically in the auditorium of Campus Biotech in Geneva or remotely by connecting to our dedicated computing infrastructure during the lectures. In addition to the evaluation, credits will only be provided for those attending live at least 80% of the lectures (remotely or physically). An email address of an official accredited university is required. A computer is required to attend the live lectures: a laptop if attending on site, a laptop or a desktop if attending remotely.

 

Attention: it is also necessary to register at https://tinyurl.com/iords2021 in addition to signing up for the course.

 

Questions: Contact https://people.epfl.ch/michael.dayan

 

Learning outcomes: To implement in Python a data science project within a Linux environment while tracking code changes with the git version control system.

 

Keywords

Data Science; Linux; Git; Python; Machine Learning

Learning Prerequisites

Required courses

None

Recommended courses

None

Dans les plans d'études

  • Forme de l'examen: Ecrit (session libre)
  • Matière examinée: Introduction to open & reproducible Data Science
  • Cours: 35 Heure(s)
  • Exercices: 35 Heure(s)

Semaine de référence