Further education in data science and machine learning // University of Oldenburg

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Analyse data in a practical way

Whether for credit risks, investments or market forecasts - machine learning is now used in many areas. It is based on analysing large volumes of data, for example from insurance companies and banks. Machine learning is a branch of the discipline of data science. At the interface of Computing Science, Mathematics and Statistics, it deals with how data can be managed, stored, processed and analysed.
In our practice-oriented module, you will learn about various methods of machine learning, both conceptual and software-supported. You will be able to analyse simulated or real data sets using models such as regression, classification and clustering and determine the quality of predictions. Aspects of trustworthy artificial intelligence are taken into account as well as requirements for data ethics and secure data storage.

Lecturer

Dr Tino Werner

German Aerospace Centre (DLR),
University of Oldenburg

Your gain in expertise

The module provides know-how and skills to ...

name requirements for machine learning methods

understand the ideas behind the regression, classification and clustering models

Train machine learning models in R

recognise the potential dangers of machine learning

evaluate a trained machine learning model fairly and objectively

interpret the results of a learning model and its predictions in a meaningful way

Further education at a glance

Certificate

University certificate

Dates

Coming soon

Time required and scope

5-8 hours per week, 6 credit points

Teaching format

Part-time, internet-based, compact practical workshops at the weekend

Prerequisites

Basic knowledge of the programming language R

Costs

1,200 euros for enrolled students or 1,500 euros for guest students plus university fee

Who is the programme aimed at?

It is aimed at anyone who works with large amounts of data and wants to analyse it in order to make predictions about possible trends or make well-founded decisions.

The module can be taken as certified further education or as part of the part-time degree programme in Risk Management and Financial Analysis. The university certificate is fully recognised for the degree course. So you can start your studies without enrolment!