CAS in Advanced Machine Learning

Mathematical Institute

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 format is designed to align with the participants’ main study and or professional activities. The teaching and learning approaches are team and discussion oriented and designed to develop practical competency. 

It is structured in six modules which are offered in blocks and Fridays' afternoon. The CAS is at a university master level and programming and some machine learning skills from eduction or profession are required, e.g. the CAS Applied Data Science.

All modules take place at the university some minutes walk from the Bern railway station. The exception is Module 3 which takes place on Mallorca at the hotel www.esblaudesnord.com.

Registration for the CAS Advanced Machine Learning 2021/22 is open.

Join information event on June 28 at 6 pm here. No registration needed.

Newly registered participants will be invited to an online information meeting with the possibility to cancel registration without any fee within one week after the meeting. 

CAS Advanced Machine Learning
Summary
Degree Certificate of Advanced Studies in Advanced Machine Learning AML University of Bern (CAS AML Unibe)
Start 08/2021
Length August 2021 - July 2022
Scope 16 ECTS
Cycle Annual
Flexible entry possible No
Single module visitable Yes
Place University of Bern, Bern Autumn School in Mallorca, Spain
Due to the pandemic situation and the related official requirements, we would like to point out that all modules can be attended online.
Language English
Admission See tab "Admission"
Cost CHF 9'600 inkl. Vollpension-Hotel in Mallorca
Special Offer Employees and Students of the University of Bern: CHF 5’600
Organising institutions Mathematical Institute
Registration

The program is organized into six modules and a CAS project work, running over 18 course days, given in blocks (August/September, and January/February) and on Friday afternoons in October, November and December. It targets professionals and researchers in the private and public sector. The content covers a review of machine learning methods, established applications, the research frontier and philosophical and ethical aspects. The difficulty is at a university master level and assumes own basic machine learning experience, programming skills and a higher education degree with some mathematical background. The program is applied in the sense of focusing on concepts and usage of common machine learning tools, not so much on theoretical elaboration of the mathematics, statistics and informatics.

Graduation is possible within one or two years. The CAS provides 16 ECTS credit points achieved in 18 days of presence with a total workload about 480 hours, including a 4 ECTS project work.

Five modules take place at the university some minutes walk from the Bern railway station. Module 3 takes place on Mallorca at the hotel www.esblaudesnord.com, a beautiful nonprofit place with focus on sustainability. Stay and full board are included in the fee.

Machine Learning Objectives

Course competence is developed throughout six modules and a CAS project work. On completion 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) 

 

If there are free places, modules can be attended individually.

Module 1: Review of machine learning, practical methodology and applications (block)

Review of basic principles, concepts, practical methodology and applications of machine learning.

 

Module 2: Deep networks (block)

Study of established deep network applications commonly used in industry.

 

Module 3: Deep learning research (block Mallorca)

Study of new promising, but not yet widely established approaches with deep networks.

 

Module 4: Selected topics on machine learning (seminar)

Participants study selected publications on machine learning and artificial intelligence and present them to the others.

 

Module 5: Philosophy and Ethics of extended cognition and artificial intelligence (Lectures and seminars)

Artificial Intelligence as a scientific field dates back to the 1950s. This module concerns key philosophical and ethical questions and discussions triggered by the existence of intelligence outside the human brain. 

 

Module 6: Elective module (Block)

One 2 ECTS module on machine learning in an applied domain, mathematical methods for machine learning and data science or entrepreneurship.

 

Project Work: 120 hours

Participants define and perform a 4 ECTS project work, individually or in teams during the CAS. Support is provided by the CAS lecturers. Output is a report, computational notebooks and a presentation. The use of own data from profession or research is encouraged.

The modules use online platforms with multimedia materials, tutorials and assessments to aid learning, along with classes for discussion, feedback and a chance to deepen knowledge. The duration of the modules corresponds to approximately 20 classroom hours each and module work (expected effort is 30 hours), with each complete module qualifying for 2 ECTS points. Main tools and CAS language are Python, TensorFlow and Git. Other tools may be used, then with limited support. Computational resources are offered.

Success Story

Click here to learn more about a case project that was developed by two of our participants as part of the CAS.

Rooms and lecturers to be confirmed. All courses take place in walking distance from the Bern railway station. The exception is Module 3 which takes place on Mallorca (stay and full board included in the fee).

Building abbreviations
Abbreviation Building 
ExWi Exakte Wissenschaften (Sidlerstrasse 5) 
UniM Uni Mittelstrasse (Mittelstrasse 43) 
HG Main Building (Hochschulstrasse 4) 
UniS UniS (Schanzeneckstrasse 1) 
VR VonRoll (Fabrikstrasse )
CAS AML Schedule 2021/22 (repeated annually)
Date Time   Room  Module  Lecturer  Comment
           
2021-02-15 18:00-19:00 Online Introduction to the CAS AML PD. Dr. S. Haug  One introduction is mandatory. No registration needed. Join online here.
2021-04-26 18:00-19:00

Online 

Introduction to the CAS AML PD. Dr. S. Haug One introduction is mandatory. No registration needed. Online here
2021-05-26 18:00-19:00 Online Introduction to the CAS AML PD Dr. S. Haug

One introduction is mandatory. No registration needed. Online here.

2021-06-28 18:00-19:00 Online Introduction to the CAS AML PD. Dr. S. Haug One introcution is mandatory. No registration needed. Online here.
           

2021-08-17 –
2021-08-20

09:00-12:30 UniM 124 M6 Mathematical Methods Dr. K. Sipos

Elective Module 6

Link to Ilias course

 

         

2021-08-24 –
2021-08-27

09:00-12:30 VR B305 M1 Review of Machine Learning, Practical Methodology and Applications    Dr. G. Conti Link to Ilias cours
           

2021-08-31 

09:00-12:30 

HG 028

M2 Deep Networks Dr. G. Conti Link to Ilias course
2021-09-01 09:00-12:30 HG 028 M2 Deep Networks Dr. G. Conti  
2021-09-02 09:00-12:30 HG 028 M2 Deep Networks Dr. G. Conti  
2021-09-03 09:00-12:30 HG 029 and HG 031 M2 Deep Networks Dr. G. Conti Attention: On 2021-09-03 we have to switch to rooms HG 029 and HG 031, as HG 028 has been reserved.
           
2021-10-04 20:00 Retreat TBC M3 Dinner at hotel Dr. Radhakrishna Achanta, Dr. Mykhailo Vladymyrov, PD Dr. Sigve Haug et al.

Arrival day.

Link to course

2021-10-05 08:00-19:30 Retreat TBC M3 Deep Learning Research    
2021-10-06 08:00-19:30 Retreat TBC  M3    
2021-10-07 08:00-12:30 Retreat TBC M3    
2021-10-08 08:00-12:30 Retreat TBC M3   Departure afternoon.
           

2021-10-22 –
2021-12-17

13:15-15:00 ExWi 228 M4 Selected Topics on Machine Learning and Artificial Intelligence (seminar)  Prof. Dr. Paolo Favaro, PD Dr. S. Haug, Simon Jenni   
2021-10-22 –
2021-12-17
15:15-17:00 ExWi 228 M5 Philosophy and Ethics of Extended Cognition and Artificial Intelligence Prof. Dr. Dr. C. Beisbart, PD S. Haug   
           
2021-11-13     CAS Project abstract submission deadline    
           

2022-02-01 –
2022-02-04

09:00-12:30  HG 028 M6 (Elective module)    
           
2021-02-13 24:00   CAS Project first version submission deadline    
           
2022-04-30 24:00   CAS Project final version submission deadline     
           
2022-06-24 24:00   CAS Completion notification    
           
 2022-07-01 17:00-21:00 ExWi Apero for finisher

 

 

 

Modules 1 to 5 are for all participant the same. In addition one has to attend one elective Module 6. 

Rooms and lecturers to be confirmed. All courses take place in walking distance from the Bern railway station. The exception is Module 3 which takes place on Mallorca (stay and full board included in the fee).

Building abbreviations
Abbreviation Building 
ExWi Exakte Wissenschaften (Sidlerstrasse 5) 
UniM Uni Mittelstrasse (Mittelstrasse 43) 
HG Main Building (Hochschulstrasse 4) 
UniS UniS (Schanzeneckstrasse 1) 
FS Fabrikstrasse 

 

CAS AML Schedule 2020/21 (repeated annually)

Date Time   Room  Module  Lecturer  Comment
           
2020-03-30 17:30-18:30 Online Introduction to the CAS AML PD. Dr. S. Haug  No registration needed.
2020-05-13 17:30-18:30

Online

Introduction to the CAS AML   No registration needed.
2020-06-29 17:30-18:30 Online Introduction to the CAS AML   No registration needed.

 

         
           
2020-08-25 09:00-12:30   M1 Review of Machine Learning, Practical Methodology and Applications    Dr. G. Conti  
2020-08-26 09:00-12:30   M1    
2020-08-27 09:00-12:30   M1    
2020-08-28 09:00-12:30   M1    
           
2020-09-01 09:00-12:30    M2 Deep Networks Dr. G. Conti  
2020-09-02 09:00-12:30   M2    
2020-09-03 09:00-12:30   M2    
2020-09-03 09:00-12:30   M2    
           
2020-09-29 08:00-19:30   M3 Deep Learning Research Dr. Radhakrishna Achanta, Dr. Mykhailo Vladymyrov, PD Dr. Sigve Haug et al.  
2020-09-30 08:00-19:30   M3    
2020-10-01 08:00-19:30   M3    
2020-10-02 08:00-12:30   M3    
           
2020-10-16

10:15-12:00 / 13:15-15:00

  M4 Selected Topics on Machine Learning and Artificial Intelligence (seminar)  Prof. Dr. Paolo Favaro, PD Dr. S. Haug, Simon Jenni  This seminars happens Tuesdays 10:15-12:00 and Fridays 13:15-15:00.
2020-10-16 15:15-17:00   M5  Philosophy and Ethics of Extended Cognition and Artificial Intelligence Prof. Dr. Dr. C. Beisbart, PD S. Haug   
           
2021-01-26 / 29

09:00-12:30

  ML for Natural Language Processing (elective module)    
           
2021-01-26 / 29 09:00-12:30    ML for imaging (elective module)    
           
2021-02-05     CAS Project first submission deadline   Instructions here
           
2021-04-30 24:00   CAS Project final version submission deadline   Instructions here
           
2021-07-02 17:00-21:00 ExWi Apero for finisher     

 

Module 1 to 5 are for all participants the same. In addition one has to attend one elective module. For 2020/21 three elective modules are offered.

The Certificate of Advanced Studies (CAS) in Advanced Machine Learning (AML) is offered by the Mathematical Institute.

Program management

  • Prof. Dr. Jan Draisma
  • Prof. Dr. Paolo Favaro
  • PD Dr. Sigve Haug (director of studies)
  • Prof. Dr. Christiane Tretter
  • Prof. Dr. Thomas Wihler (chair)

Lecturers            

  • Prof. Dr. Dr. Claus Beisbart - University of Bern
  • Dr. Melanie Graf - University of Basel
  • PD Dr. Sigve Haug - University of Bern
  • Dr. Alexander Kashev - University of Bern
  • Dr. Kinga Sipos - University of Bern
  • M.Sc. PabloVerges   - DECTRIS Ltd.
  • Dr. Mykhailo Vladimirov - University of Bern
  • Dr. Guillame Witz - University of Bern
  • Prof. Dr. Kai Brunnler - Berner Fachhochschule
  • Prof. Dr. Geraldine Conti - REDS - HEIG-VD and PAG

The CAS is at a university master level and programming and some machine learning skills from eduction or profession are required, e.g. the CAS Applied Data Science.

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).

SUITABLE FOR MANAGEMENT ► wanting to know how machine learning   is performed, limitations and possibilities, ethical aspects

RELEVANT FOR DATA ANALYSTS ► wanting to deepen and update their machine learning skills

APPLICABLE TO CONSULTANTS ► with a desire to know and exploit the possibilities offered by machine learning methods

INTENDED FOR RESEARCHERS ► wanting to extend the machine learning application in their field

Standard data sets are provided, but participants are encouraged to bring or acquire their own. If you have any questions regarding whether this program could work for you, please do not hesitate to contact us.

Admission requirements

  • A university degree and basic knowledge of mathematics, statistics, programming, machine learning and professional or research experience in the field of data analysis are required for admission to the course. 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.
  • Interested parties who only want to take part in individual modules can be admitted, provided that there are free course places.

The program management decides on admission to the course. There is no entitlement to admission.

Program fees

Regular CAS program: CHF 9'600

Employees & Students of University of Bern: CHF 5'600

Inclusive of all modules, performance assessments, certificates, materials & teaching platforms, coffee breaks, full pension hotel in Mallorca (Module 3: stay and full board are included in the fee) and diploma apero. Participants must supply their own laptops.

If there are free places, modules can be attended individually. Prices are CHF 300.- per half day. Individual modules are accredited with certificates which are accumulated for the full CAS AML

Registration

 

Success Story

Click here to learn more about a case project that was developed by two of our participants as part of the CAS.

Contact

Vorherige