COM-598 / 30 crédits

Enseignant: Profs divers *

Langue: Anglais

Withdrawal: It is not allowed to withdraw from this subject after the registration deadline.


Summary

The student carries out an academic or industrial master's project. The student will use the required skills and knowledge to accomplish an independent Master in Data Science.

Content

The Master's project gives the student's the opportunitiy to carry out theoretical and practical work of academic or industrial scope registered in a broad field of knowledge of the engineer in Data Science acquired during his years of study. Each project is carried out under the supervisor of a professor from the Computer and Communication School.

Learning Outcomes

By the end of the course, the student must be able to:

  • Formulate and deal with complex subjects in a critical, independent and creative way by applying a holistic life
  • Plan and use the appropriate methods to carry out tasks within a given framework
  • Develop an individual research project
  • Apply skills to a specific subject
  • Represent datain a coherent and efficient way
  • Develop expertise in a specific area of research
  • Compose a written scientific report of a project
  • Orally present a project for a scientific audience

Transversal skills

  • Set objectives and design an action plan to reach those objectives.
  • Use a work methodology appropriate to the task.
  • Communicate effectively, being understood, including across different languages and cultures.
  • Assess progress against the plan, and adapt the plan as appropriate.
  • Give feedback (critique) in an appropriate fashion.
  • Take feedback (critique) and respond in an appropriate manner.
  • Collect data.
  • Access and evaluate appropriate sources of information.

Teaching methods

The student will have to write a report of his master's project which will be evaluated by a jury during the oral defense of his work.

Assessment methods

Written report and oral presentation

Dans les plans d'études

  • Semestre: Automne
  • Forme de l'examen: Oral (session d'hiver)
  • Matière examinée: Master project in Data science
  • Projet: 900 Heure(s) par semestre
  • Type: obligatoire
  • Semestre: Printemps
  • Forme de l'examen: Oral (session d'été)
  • Matière examinée: Master project in Data science
  • Projet: 900 Heure(s) par semestre
  • Type: obligatoire

Semaine de référence

Cours connexes

Résultats de graphsearch.epfl.ch.