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Advanced Machine Learning

CAS

Universität Bern UNIBE

Catégories
Lieu de formation

Berne (BE)

Langue d'enseignement

anglais

Type de formation

Hautes écoles universitaires HEU - Formation continue: formations longues

Modalités temporelles

En emploi

Thèmes de formation

Nature, sciences naturelles

Domaines d'études

Mathématiques

Swissdoc

7.160.5.0

Mise à jour 10.02.2021

Description

Description de la formation

In many disciplines, the amount of available data and the computing capacity are growing rapidly. This enables the application of machine learning methods on tasks previously being reserved for humans. Trained machines outperform homo sapiens in more and more cognitive tasks. As with other disruptive technology emergences, the resulting automation potential represents a huge benefit for the human society, but also comes with new challenges and risks.

The CAS is structured in six modules:

  • Review of machine learning, practical methodology and applications (block)
  • Deep networks (block)
  • Deep learning research (block Mallorca)
  • Selected topics on machine learning (Seminar)
  • Philosophy and Ethics of extended cognition and artificial intelligence (Lectures and Seminars)
  • Elective module (block)
  • Project Work

Scope: 16 ECTS

Objectives

The graduates will (be able to):

  • design, tune, train and measure performance of neural networks with advanced deep learning libraries
  • understand the inner mechanisms of neural networks during training
  • familiar with active research in machine learning
  • understand and communicate scientific publications on machine learning and artificial intelligence
  • familiar with the philosophy and ethics of extended andartificial intelligence
  • familiar with one or more applied machine learning domains, the main mathematical methods for data science and machine learning or basic entrepreneurship (elective module) 

Admission

Conditions d’admission

  • university degree
  • basic knowledge of mathematics, statistics, programming, machine learning and professional or research experience in the field of data analysis. The required basic knowledge is based on the level of an introductory lecture as part of an undergraduate master’s degree. The program management specifies these requirements.

Exceptions to the admission requirements can be approved by the program management “sur Dossier”. For people without a university degree, they can impose additional requirements for admission to ensure that they can successfully complete the course.

Target groups

Aimed at students and professionals from the public and private sector that hold a degree from a university or a university of applied sciences (e.g. BSc, MSc, PhD).

Coûts

CHF 9'600.- (incl. full pension hotel in Mallorca)
Employees and students of the university of Bern: CHF 5'600.-

Diplôme

  • Certificate of Advanced Studies CAS

Certificate of Advanced Studies in Advanced Machine Learning, University of Bern

Infos pratiques

Lieu / adresse

  • Berne (BE)

Autumn School in Mallorca, Spain

University of Bern
Mathematical Institute
Sidlerstrasse 5
3012 Bern

Déroulement temporel

Début des cours

August 2021

Durée de la formation

1 year
(18 course days, given in blocks and on Friday afternoons)

Modalités temporelles

  • En emploi

Langue d’enseignement

  • anglais

Remarques

Interested parties who only want to take part in individual modules can be admitted, provided that there are free course places.

Liens

Renseignements / contact

Sigve Haug, sigve.haug@math.unibe.ch, +41 31 631 82 46
Claire Dové, claire.dove@math.unibe.ch, +41 31 631 80 85

Universität Bern UNIBE

Zulassung, Immatrikulation und Beratung
Tel.: +41 31 684 39 11

orientation.ch