CAS in Applied Data Science

With the explosion of data in science, economics, administration, medicine and many other fi elds, the importance and the demand for data science skills are increasing. Data science is a discipline consisting of applied mathematics, statistics, computer science, ethics and subject specifi c knowledge in application areas. It is the scientifi c methods and processes of extracting knowledge and insights from data. In light of this, the University of Bern off ers a Certificate of Advanced Studies (CAS) program in Applied Data Science. The program is organised into six modules, running over 21 course days from August to January and targets professionals and researchers in the private and public sector. The content covers a full cycle from data acquisition planning, description and visualisation of data, inference, machine learning, best practices ethics and deep learning. Our teaching methods are modern and peer oriented. The level assumes own experience and a higher education degree with some mathematical background. The program is applied in the sense of focusing on concepts and usage of common data science infrastructures and software tools, not on theoretical elaboration of the mathematics, statistics and informatics

Objectives

Course competence is developed throughout six modules. On completion the graduates will:

• be familiar with different data sources, data types, and be able to develop data management plans;
• be able to describe, extract and present scientific knowledge from data by application of statistical methods;
• be able to process data with 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 use a wide range of data science tools and methods;
• be able to perform deep learning for a wide range of tasks.

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

Module 1: Data Acquisition and management

In this block module, you will learn to understand different data sources and types and how to design data management models and plans.

Module 2: Statistical inference for data science

In this block module, you will become familiar with typical statistical concepts for describing and analysing data. You will learn the importance of statistical inference for data science and where to apply it, along with the understanding and application of the theoretical concepts. You will learn how to draw scientific conclusions from statistical analysis results.

Module 3: Data analysis and machine learning

In this module, you will learn about standard analysis techniques and how to apply state-of-the-art machine learning with Python.

Module 3 traditionally takes place at the mediterranean coast. Full pension hotel accommodation is included in the CAS fee. 

Module 4: Ethics and best practices

In this module, we reflect upon and apply best practices for data and code management, resource usage, quality assurance, open science, open access and fair principles. You will learn about and be able to discuss the ethical questions in scientific computing, and learn to use Version Control Software with Git.

Module 5: Peer Consulting and Selected Readings

This module comprises This module comprises peer knowledge exchange groups, peer consultations and selected readings.

Module 6: Deep Learning

In this module, you will learn performing deep learning with TensorFlow.

Module 6 traditionally takes place in the wonderful historic hotel Regina in the ski resort Mürren (Bernese oberland), only about two train hours from Bern. Full pension hotel accommodations are included in the CAS fee. 

All modules

The duration of all modules corresponds to approximately 20 classroom hours each and module work (expected eff ort is 30 hours), with each complete module qualifying for 2 ECTS points. The expected workload for the CAS Project is 120 hours. Main tool and language is Python.

Information Events

Learn everything you need to know about the CAS in Applied Data Science. One introduction is mandatory, remote participation is possible. 

Introductionary self-study pre-courses

To prepare yourself for the CAS Modules we offer the following two online self-study pre-courses:

• Introduction to Python: Log in to Ilias to start

• Mathematical Methods (MM): Log in to Ilias to start 

We recommend the pre-course in MM specifically for ADS & AML participants and to start the self-study in week 32.
For NLP, AICP & AI4T participants we recommend the Python pre-course and to start the self-study in week 32.

Introduction to Python takes approx. 1 day to finish.
Mathematical Methods takes approx. 4 days to finish.

We offer Q&A sessions for both courses:

• Intro to Python: 11.08.2025, 4:00 - 6:00 pm, online, Zoom Link is on Ilias.
• MM: 13.08.2025, 4:00 - 6:00 pm, online, Zoom Link is on Ilias.

• MM: 15.08.2025, 4:00 - 6:00 pm, online, Zoom Link is on Ilias.

Please add your questions to the Google-Forms on Ilias latest 3 days before the Q&A session!

DSL Crash-course in Data Science with Python

This is a four days in-person crash-course in Data Science with Python

Attendance is recommended (but not required) for CAS NLP, AICP & ADS students who wish to refresh their Python programming knowledge
or who are new to the Python programming language and who think that the self-study course (above) won't be enough for them.
The goal of the course is to acquire the necessary basic knowledge to allow you to then follow more advanced courses like a CAS.

Prerequisites:

• Participants must bring own laptops
• No previous knowledge in Python is necessary. Exposure to any other programming language or programming concepts (variables, loops) is of benefit but not strictly required.

Certificate:

• A certificate will be delivered to participants who have attended the whole training.

If you want to participate please sign up for the course below. 

Modules

All Information about Modules 1-6. 

Course materials are accessed via the Ilias learning platform upon receiving the password. 

Events and other important dates

Information Events

Learn everything you need to know about the CAS in Applied Data Science. One introduction is mandatory, remote participation is possible. 

Introductionary courses

Prepare yourself for the CAS Modules. We offer the following introductionary courses to refresh your knowledge.

Modules

All Information about Modules 1-6. 

Course materials are accessed via the Ilias Learning Platform upon receiving the password. 

Events and other important dates

The Certificate of Advanced Studies (CAS) in Applied Data Science (ADS) is offered by the Mathematical Institute.

Program management

• Prof. Dr. Jan Draisma 
• Prof. Dr. Tobias Hodel
• 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 
• Prof. Dr. Kai Brunnler 
• Dr. Geraldine Schaller Conti 
• PD Dr. Sigve Haug 
• Dr. Kinga Sipos 
• Dr. Anja Mühlemann
• Dr. Mykhailo Vladymyrov 
• Dr. Aris Marcolongo
• MA Ahmad Alhineidi
• et al. 

Target groups

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

SUITABLE FOR APPLICATION ORIENTED PROFESSIONALS ► Make your own applications with your own data

RELEVANT FOR DATA ANALYSTS ► Go beyond spread sheets towards large data sets and refine their skills

APPLICABLE TO CONSULTANTS ► Know the possibilities offered by data science

INTENDED FOR RESEARCHERS ► Take data science expert roles within your teams

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

Registered participants will receive acceptance confirmation by email and will be invited to one of the next information events. Attendance to one information event is mandatory. Participants can cancel their registrations before the deadline without any costs. After the deadline the regulations apply. Individual modules and electives can be attended before the registration. Please contact PD Dr. Sigve Haug for further information.

Registration opens in December and a maximum of 20 registrations can be accepted each year. Registrations are processed in the order of arrival. The CAS can only be offered if there are sufficient registrations by the cost-free cancellation deadline below.

Cost-free cancellation until: 30.6.2025

Per year there are 20 places. Registrations are accepted in the order they arrive. A waiting list is maintained. 

Program fees

Regular CAS program: CHF 9'600.-

Students currently enrolled in an University or University of Applied Sciences: CHF 5'600.-

Employees of University of Bern: CHF 5'600.-

Payment in installments is possible.

lnclusive of all modules, performance assessments, certificates, materials & teaching platforms, coffee breaks, full pension hotels (Module 3 and Module 6) and diploma apero.

Participants must supply their own laptops.

lf 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 ADS.

Register here