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MScData Science and Engineering

University of Applied Sciences Upper Austria
Austria, Steyr / Wels / Hagenberg / Linz
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fh-ooe.at/..r/data-science-und-engineering 

Overview

Interested? To learn more about this study programme, entry requirements and application process, please contact one of our consultants in a country nearest to you.

Programme structure

The master’s degree in data science and engineering with two specializations in biomedical data analysis or data analysis in marketing and production is not only focused on the technical and mathematical aspects of data science. It also prepares the graduates for the future professional field of data scientists by deepening their interdisciplinary knowledge from the application domains.

Focus of the training

_Structure of data understanding: data selection, data integration and data preparation, linking, transformation and indexing of various data sources, development of meaningful data representations and visualizations
-Data storage and management in combination with big data and cloud technologies, also for real-time data
-Data analysis with methods from the areas of computational intelligence and statistics for the creation of forecast models to answer a specific question from the company
-Computer vision methods for extracting knowledge from image data
-Practice-related projects for data analysis with cooperation partners from the domains of biomedicine, marketing and production

Career opportunities

Graduates of the master’s degree in Data Science and Engineering are able to generate information from large amounts of data and derive recommendations for action that enable the company to work more efficiently. To do this, they use innovative analysis methods and develop queries that generate valuable information from confusing amounts of data. Subsequently, hypotheses are derived, which are checked and prepared for management as a basis for decision-making.

The aim is to train data scientists as data architects with strategic vision, well-founded analytical skills and distinctive technical competencies and to prepare them for taking on demanding tasks in the data science and big data environment.

-Analysis of data or data models, IT landscapes and business processes with regard to the need and the introduction of new approaches to knowledge extraction
-Design of processes for extracting, cleaning and transforming data
-Modeling of data schemes for the integration and analysis of data
-Use of data mining and statistical methods as well as development of forecast models
-Conception of solutions for processing and analyzing data in real time using the latest analytical tools and big data technologies
-Visualization of data and preparation of analytical findings
-Communication, development and presentation of solutions to the decision-makers (specialist departments and management)

Apply now! Fall semester 2022/23
Application period has ended
Notes
Please see the university profile or contact us for the deadlines that apply to you

Application deadlines apply to citizens of: United States

Apply now! Fall semester 2022/23
Application period has ended
Notes
Please see the university profile or contact us for the deadlines that apply to you

Application deadlines apply to citizens of: United States