Machine Learning and Data Analytics

In the Master's degree program in Machine Learning and Data Analytics, you will learn which methods are available for machine learning and how to apply them correctly and efficiently. From data storage, especially of large amounts of data, to data evaluation and decision-making, you will come into contact with all steps of data analysis.
Both symbolic learning methods such as inductive and deductive learning and sub-symbolic techniques such as support vector machines or neural networks are covered. In doing so, they acquire a fundamental understanding of theory and practice. The ethical and social aspects also play a decisive role in this area and are considered as part of the course, as our working world will change fundamentally through the application of machine learning methods.

Building on the skills of the Bachelor's degree

A special feature of the course is the so-called competence area. Depending on the Bachelor's degree with which you begin your studies, you then choose your area of expertise in the Master's degree. There, you will attend two lectures from Aalen University's Master's program that are typical for the application of machine learning methods in your field. In this way, you will come into contact with the applications from your later professional life at a very early stage.

Formal requirements

Bachelor's degree with at least 7 semesters standard period of study (210 CP):

To study the Master's degree program in Machine Learning and Data Analytics, you need ...

 ... a professionally qualifying university degree (bachelor's degree, diploma degree or equivalent) in a degree program with a focus on computer science, business informatics or a related field with an above-average grade of at least 2.5 and at least 210 ECTS credit points.

OR

... a professionally qualifying university degree (Bachelor's degree, Diplom degree or equivalent) in a degree program in the fields of electrical engineering, mechatronics, mechanical engineering, business administration or a related field with an above-average degree with a grade of at least 2.5, with at least 210 ECTS credit points and in conjunction with proof of previous university-equivalent knowledge in the field of computer science and/or business informatics or related fields amounting to at least 20 CP or comparable achievements in the above-mentioned fields.

Bachelor's degree with at least 8 semesters standard period of study (less than 210 CP):

Applicants with a university degree with fewer than 210 ECTS credit points but at least 180 ECTS credit points (from the areas listed above) are only admitted on condition that they acquire the difference up to the required 210 ECTS credit points during their Master's degree program. The form in which the additional credits are to be earned is decided by the person responsible for admission. In this case, the course will be extended by one semester.

Requirements for foreign students:

Applicants whose native language is not German must provide proof of the required German language skills with their application. Proof of German corresponding to level B1 according to the Common European Framework of Reference for Languages is provided by the Goethe-Institut test or an equivalent test.

The fields of activity in professional life are as diverse as the applications of machine learning. From application to development to research, you are qualified for all areas. Practically all sectors are open to you. The Master's degree also enables you to begin a doctorate if you wish to pursue an academic career.