Lucerne’s MSc data science program shines with SAS specializations


Lucerne's University of Data Science and Arts launched its MSc in Applied Information and Data Science in autumn 2018. Since then, the program has had a positive response from both the industry and the market, as well as from its students. This year, it offers new options that should make it even more attractive to both students and potential employers or partners.

Currently, there are around 250 students enrolled in the program across all years. In autumn 2020, the program started its third year and welcomed over 100 new students. The program is designed to help students become the data scientists of the future. It exposes them to real-world problems and data, as well as teaching a full-stack data science approach.

An ongoing issue

It has long been recognized that there are issues with how students are taught data science. In particular, teaching data sets are designed to enable students to develop skills in handling data. They are therefore usually complete and clean. However, real-world data is often incomplete, dirty or plain unreliable. In real life, data scientists may spend considerable amounts of time simply finding suitable data and pulling it together from multiple sources, which is not really an issue that students encounter. Many courses also focus more on the techniques themselves and less on how to solve problems with them. The application and problem solving, however, is what most businesses want from analytics.

Data scientists also need to be more than "just" analysts. In a recent article, Adriana Rojas described four data science profiles that were important in business. The first was business translator, working between and across business and analysts to translate demands and results between the two. The second was the citizen data scientist, the business user with an understanding of data science who could do some analytics themselves. The third area of interest focused on data compliance, and how to ensure that analytics is used wisely and well. Finally, there are those focused on customer success, helping their customers to get the most from technology through their knowledge and insights. These requirements place a big demand on university courses in data science.

Setting Lucerne apart

As the name suggests, Lucerne’s MSc distinguishes itself from other data science master's programs by focusing on applied approaches. There is a huge, and growing, demand in the market for people who can offer full-stack data science skills in a practical way – and that is what this program provides.

What’s more, the program has been extended this year by the addition of a SAS specialization. This is an integral part of the course, and students can choose two elective SAS modules, Visual Business Analyst and Machine Learning Specialist. Both modules are flexible and combine an e-learning approach and web-based software access, including exam preparation guides. Students sit a module exam, and passing the exam provides three educational credits for each module.

If the students decide to also do the master's thesis with SAS technologies, they will get a kind of “dual degree” as SAS provides them the Joint Certification Badge. The master's thesis is a major part of the program and is worth 24 educational credits. Students undertake a real-world analytics team project, using real data, with all the problems and issues that they would encounter in business. Thus it gives them essential preparation for working in data science in industry or business. This thesis gives students the additional certification Joint Certificate in SAS Visual Analytics and Machine Learning Expert. This is proof – if anyone needs it – that these students have the necessary skills to work as data scientists in the real world.


About Author

Markus Grau

In my role as "Academic Program Manager" I establish and enable trust- and successful business relations between Academic Institutes, the industry and SAS. It is my passion to consult and support Professors, Lecturers and Students in their endeavors to make use of AI, Business- and Visual-Analytics, Data Science and Machine Learning for better, fact-based decision making. I studied computer science and I am holding an MBA with focus in Marketing and Communications Management. Also I am a lecturer at Luzern University of Applied Sciences. My broad and extensive business knowledge results from various positions, such as Business Analyst, Marketing- , Partner- and Program-Manager, as well as Sales Representative, in firms like Sunrise, Hewlett-Packard and other leading industry-bluechips.

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