نظرة عامة على البرنامج

Master Data Science Program

The Master's program in Data Science aims to provide a practically oriented and scientifically founded education in the field of modern Data Science. Data Science is a crucial driving force in today's digital world, with vast amounts of data being captured and generated in almost all areas of the economy.

Program Objectives

The program's objective is to equip students with the skills to gain insights from large datasets, which can add value to their respective fields. This requires not only the development of efficient algorithms but also a fundamental understanding of the interpretability and reliability of the results. The program covers a wide range of competencies, including practical handling of large datasets, a solid mathematical and statistical foundation, and expertise in the respective application area.

Program Structure

The Master's program in Data Science is a four-semester program with 120 ECTS credits. The program is taught in English, and the degree awarded is a Master of Science (MSc). The program is a joint venture between the faculties of Economics, Computer Science, Mathematics, and Historical and Cultural Studies.

Curriculum

The curriculum includes courses in:

• Machine Learning
• Mathematical and Statistical Foundations
• Optimization Methods
• Mining Massive Data
• Visual and Exploratory Data Science

Admission Requirements

English language proficiency at level B2 of the Common European Framework of Reference for Languages (CEFR) is recommended.

Program Details

• Duration: 4 semesters
• Credits: 120 ECTS
• Degree: Master of Science (MSc)
• Language: English
• Study code: 066 645
• Program leadership: SPL 5 (Computer Science and Business Informatics)

Joint Venture

The Master's programs in Business Analytics, Data Science, and Digital Humanities are a joint offer from the faculties of Economics, Computer Science, Mathematics, and Historical and Cultural Studies. More information on the joint study program in the field of Data Science can be found on the pages of the Data Science @ Uni Vienna research association.