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Classes are scheduled on Thursday and Friday, and there can be up to 10 lessons per day. In addition, you will need to plan enough time for studying and doing the exercises, which may vary greatly depending on how familiar you are with the topics and based on the period you chose in which to complete the programme. Experience has shown that students in the most concentrated form of the programme need to plan around 20 hours a week, in addition to the time spent in class.
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The programme includes certain preparatory modules in which students learn the basics of computer science and statistics. Those who can document having a background in these areas can have some of their prior work converted into credits to be applied towards their degree. In contrast to other programmes, our Master's course does not require previous academic work in these disciplines and is basically open to anyone with a background in the social sciences, natural sciences and humanities. It also places a strong emphasis on the Master's Thesis, which can be combined easily with a professional activity or an internship.
There is no hard and fast rule here. You have a lot of freedom in scheduling your daily study routine, but you must reserve two days a week for classes. This means you can freely schedule your work and leisure time, leaving you with enough time to work while studying. We recommend that you plan your workload during semester carefully to ensure there is enough time for your studies and for relaxation. Don’t hesitate to contact the programme head if you have questions or need advice.
Prolonging the total period of your studies will reduce the workload per semester proportionally. However, you will still need to attend classes on two days, although you will have longer gaps in between.
The Master’s programme promotes learning that immerses students in the applied world of data science. This means you are eligible for a certain number of credits for activities in a data-related field relevant for your coursework – provided you can demonstrate that they are sufficiently relevant. The decision of whether to grant such credit rests with the programme head.
The programme allows you to attend modules offered by external partners (e.g. Global School of Empirical Research Methods (GSERM) at the University of St. Gallen, some modules at the University of Lucerne, certificate courses at SAS, etc.). Other offers are being considered as well. Attendance of such courses can help you to meet the requirement in your core electives. Please contact the programme head in advance if you have any questions in this connection.
Data science is an interdisciplinary field that plays an increasingly important role in a range of occupations. The Master’s programme is therefore open to anyone, which implicitly means that students will have a wide variety of backgrounds in these subjects. The programme is based on the competencies that Bachelor's students of business administration typically acquire at a university of applied sciences or a university in Switzerland. If you are new to these fields, you must be willing to learn the basics during the first semester, and the respective preparatory modules therefore count as part of the programme.
We will help you with arranging a semester abroad but recommend that you go at the earliest in the third semester. While Lucerne University of Applied Sciences and Arts has an extensive network of partners, the International Office also helps students with preparing for their semester abroad outside of this network.
