Applied Data Science: Machine Learning

Diplôme / certificat de l’institution de formation

Ecole polytechnique fédérale de Lausanne (EPFL) > EPFL Extension School

Lieu de formation

A distance

Langue d'enseignement


Type de formation

Formation continue: formations longues

Modalités temporelles

À la carte

Thèmes de formation

Études et formations en informatique


7.566.2.0 - 7.563.2.0

Mise à jour 10.05.2021


Description de la formation


  • Give the students hands-on experience in one of the hottest areas of data science
  • Learn techniques and tools for data acquisition, transformation and predictive analysis, ensuring having a solid foundation in working with the entire data pipeline

15 ECTS credits will be awarded to learners who successfully complete the program.

Plan de la formation

The program includes four certified courses and a customizable capstone project:

  • Introduction to Data Analysis with Python
  • Applied Data Analysis
  • Applied Machine Learning 1
  • Applied Machine Learning 2
  • Capstone Project


Conditions d’admission

This course is taught at intermediate level. The students should have the following skills and abilities prior to registering for this course:

  • English at B2 level
  • A computer with a webcam, microphone and a minimum internet connection of 2Mbps download / 512kbps upload, enabling you to stream videos with sound and to effectively participate in video chats
  • Basic understanding of algebra, geometry, calculus (derivatives), probability and statistics
  • Familiarity with computer environments (what is a program, file system, file formats, terminal, programming language library)
  • Prior experience with any programming language

Lien sur l'admission


CHF 490.- per month


  • Diplôme / certificat de l’institution de formation

Learners who successfully complete the program earn an EPFL COS (Certificate of Open Studies) Diploma.

Infos pratiques

Lieu / adresse

  • A distance

Déroulement temporel

Début des cours

We enroll learners in this course on a rolling basis.

Durée de la formation

450 hours.
Self-paced, online learning.
Learners will move through the coursework most easily when they can commit to a minimum of 5-10 hours per week.

Modalités temporelles

  • À la carte

Langue d’enseignement

  • anglais