DAS in Extended Intelligence
The DAS Extended Intelligence is a university study program leading to a «Diploma of Advanced Studies in Extended Intelligence» awarded by the University of Bern (DAS XI Unibe). In addition to the learning objectives of the CAS programs in Applied Data Science (CAS ADS) and Advanced Machine Learning (CAS AML), the participants are within their DAS thesis work able to independently design, carry out and communicate an Extended Intelligence project with current Machine Learning methods on a publication-ready level. The learning methods include lectures, online courses, seminars, workshops, events and individual work with extended intelligence tools, typically with data science and machine learning software libraries.
|Diploma of Advanced Studies in Extended Intelligence (DAS XI Unibe)
|Flexible entry possible
|Single module visitable
|University of Bern. We would like to point out that every module can be visited hybrid (on-site or online).
|Prerequisite for admission to the program is successful completion of the CAS AML as well as the CAS ADS. These must not date back more than five years (date of degree certificate).
About the program
The DAS Extended Intelligence is a university study program leading to a «Diploma of Advanced Studies in Extended Intelligence». The program comprises at least 38 ECTS credits. It consists of the CAS ADS study course (16 ECTS), the CAS AML study course (16 ECTS), a DAS module (2 ECTS) and a DAS thesis (4 ECTS). In the DAS thesis, a topic from one of the topic from one of the two CAS programs is discussed or topics from the two CAS from both CAS programs are deepend in an interdisciplinary way.
The study programs make use of different teaching methods, in order to optimally support the transfer of learning and knowledge and to ensure a lively learning culture. In addition to imparting theory- and practice-oriented knowledge and skills, the courses offer space for reflection and discussion. The content and form of the courses take into account the needs and wishes of the participants. Their professional knowledge and their experience as experts flow into the teaching and learning process..
The courses of study are aimed at people who are interested in management and analysis of data, especially in the field of machine learning and learning and artificial intelligence, and who want to update their want to update and round off their knowledge through and round off their knowledge.
Course Competencies: Extended Intelligence
- Be familiar with various data sources and data types and be able to develop data management plans
- Be able to describe, extract, and present scientific findings from data by applying statistical methods
- Be able to process data using machine learning tools and methods
- Be familiar with best practices for data management, analytics, and science;
- Be able to analyse and communicate data science challenges and apply a wide range of data science tools and methods;
- Be able to perform Deep Learning for a variety of tasks;
- Know an overview of machine learning methods and applications.
- Apply and train Deep Neural Networks
- Be familiar with recent methods for Deep Neural Networks
- Overview current research topics in the field of Deep Neural Networks
- Be able to argue about the ethics and philosophy of artificial and extended intelligence
- Carry out a project in the field of Extended Intelligence
Further learning objectives
In addition to these learning objectives, within the framework of their DAS work they will be able to independently an extended intelligence project using current methods of methods of machine learning, and to communicate it at a level and communicate it at a level that is ready for publication.
The study program will be conducted in English.
The DAS program comprises a total of at least 38 ECTS credits and has a modular structure.
It is composed of:
- the CAS AML (16 ECTS credits),
- the CAS ADS (16 ECTS credits),
- a DAS module worth 2 ECTS credits,
- a DAS thesis worth 4 ECTS credits.
Organising institution and faculty
The Diploma of Advanced Studies (DAS) in Extended Intelligence (XI) is offered by the Mathematical Institute of the University of Bern. The individual courses are taught by university lecturers and experienced experts from the field. Usually, these experts also supervise the final theses.
- Prof. Dr. Jan Draisma (chair)
- Prof. Dr. Paolo Favaro
- PD Dr. Sigve Haug (director of studies)
- Prof. Dr. Christiane Tretter
- Prof. Dr. Thomas Wihler
The DAS in Extended Intelligence is designed for students and professionals in the public or private sector who have graduated from a university or college. It is aimed aimed at people who are interested in management and analysis of data, especially in the field of machine learning and learning and artificial intelligence, and who want to update and round off their knowledge.
Prerequisite for admission to the DAS XI course is successful completion of the CAS AML as well as the CAS ADS. These must not date back more than five years (date of degree certificate).
Application and tuition fees
DAS XI: CHF 3'000. In addition, the are the costs of the preceding CAS courses.
MAS in Extended Intelligence
The modular continuing education program Extended Intelligence is designed for graduates of all disciplines who want to significantly expand their skills in data science, machine learning and statistics.
CAS Applied Data Science
Data Science ist eine Disziplin, die angewandte Mathematik, Statistik, Informatik, Ethik umfasst. Der Studieninhalt deckt einen vollständigen Zyklus von der Planung der Datenerfassung über die Beschreibung und Visualisierung von Daten bis hin zu Schlussfolgerungen und Best Practice-Beispielen für maschinelles Lernen und Ethik ab.
CAS in Advanced Machine Learning
This CAS AML offers the opportunity to complement your data science competences with a formal deepening and broadening of knowledge and skills on machine learning and artificial intelligence.
CAS Advanced Statistical Data Science
Aufbauend auf den Vorkenntnissen aus dem CAS in Statistical Data Science (oder äquivalenten Vorkenntnissen) lernen die Teilnehmenden fortgeschrittene und spezialisierte statistische Methoden und Modelle kennen.