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Advanced Machine Learning

CAS

Universität Bern UNIBE

Kategorien
Ausbildungsort

Bern (BE)

Unterrichtssprache

Englisch

Ausbildungstyp

Universitäre Hochschulen UH - Weiterbildung: Lehrgänge

Zeitliche Beanspruchung

Berufsbegleitend

Ausbildungsthemen

Natur, Naturwissenschaften

Studienrichtungen

Mathematik

Swissdoc

7.160.5.0

Aktualisiert 15.12.2023

Beschreibung

Beschreibung des Angebots

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.

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) 

Aufbau der Ausbildung

The CAS is structured in six modules:

  • Review of machine learning, practical methodology and applications (block)
  • Deep networks (block)
  • Advanced Models I (block Camogli) 
  • Selected topics on machine learning
  • Philosophy and Ethics of extended cognition and artificial intelligence (Lectures and Seminars)
  • Advanced Models II (block Mürren)

Scope: 16 ECTS

Voraussetzungen

Zulassung

  • 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).

Kosten

CHF 9'600.- (Full pension hotel accommodation is included in the CAS fee)
Employees and students of the university of Bern: CHF 5'600.-

Abschluss

  • Certificate of Advanced Studies CAS

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

Praktische Hinweise

Ort / Adresse

  • Bern (BE)

University of Bern; Mürren, Bernese Oberland (Module 6); Camogli, Liguria, Italy (Module 3)

University of Bern
Mathematical Institute
Sidlerstrasse 5
3012 Bern

Zeitlicher Ablauf

Beginn

August

Dauer

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

Zeitliche Beanspruchung

  • Berufsbegleitend

Unterrichtssprache

  • Englisch

Bemerkungen

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

Links

Auskünfte / Kontakt

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

berufsberatung.ch