Lucerne University of Applied Sciences and Arts
Master of Science in Applied Information and Data Science
Lucerne, Switzerland
MSc
DURATION
8 semesters
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
01 Dec 2025*
EARLIEST START DATE
Feb 2026
TUITION FEES
CHF 1,300 / per semester **
STUDY FORMAT
Blended
* Application deadline for spring semester: 1 September for applicants requiring a visa | 1 December for Swiss and EU/EFTA applicants.
** Application fee: CHF 250 | Semester fees for foreign students: CHF 1,300 | Semester fees for Swiss students: CHF 800 | Plus additional study-related costs
Key Summary
Understanding the potential of Artificial Intelligence (AI) & data and using it professionally
Data is the resource of the 21st century and the quest for harnessing its economic and social potential calls for an increasing number of specialists and managers who not only have solid technical and analytical skills but are also able to apply them as creative entrepreneurs. The ability to recognize relationships in large data sets and to unleash their value is increasingly becoming a key competence that companies and organizations are eager to acquire, resulting in a strong demand for talented experts who can use this potential to the best effect.
Our multidisciplinary Master's program in Applied Information and Data Science prepares its students for the challenges they will face as specialists and managers in the digital economy. As data scientists with strong applied skills, they will have a wide range of career options in SMEs, corporations, public institutions, and non-profit organizations.
What makes us special or why you should choose us to get the "big picture"
It’s open to career-changers
The fields of data science today are as varied as the disciplines in our students’ academic background (social sciences and economics, natural sciences, engineering, humanities). Accordingly, the Master's programme is designed for ambitious individuals with a university degree, a strong interest in data technologies and above-average analytical abilities.
Future-oriented technologies & Artificial Intelligence (AI)
Artificial Intelligence is playing an increasingly important role in data analysis and decision-making. Our master's program not only teaches traditional data science methods but also integrates cutting-edge AI technologies to identify complex patterns, enhance predictions, and develop innovative solutions. Students learn to apply AI models in practice and to handle this key technology of the future responsibly.
It’s flexible and individual
Students have a great deal of flexibility in designing their studies, and they can determine the start, duration and course load based on their individual needs.
It’s designed for practitioners
Our data specialists are highly competent in using the right queries, interpreting the hidden information in data, and gaining insights for forecasting trends and events – with a view to helping management teams, organisations and society make better decisions. To this end, the Master's programme provides future data specialists not only with deep expertise in their field but also with consummate skills for applying it for optimal benefit. By working on projects, they will further develop their knowledge by tackling real-life problems as found in a wide range of applied fields.
The Big Ten - What it Needs to become a Great Data Scientist
- Questioning and thinking about data
- Collecting, integrating, and preprocessing data
- Processing, exploring, analyzing, and interpreting data
- Predicting the behavior of people and systems
- Visualizing and telling stories about data
- Designing and managing data projects
- Developing data-driven business models
- Designing data products and services
- Applying data in a wide range of fields
- Understanding legal and ethical issues
Contents of the Master’s Program
Our Ten Main Topics
- Management of Digital Enterprises and Digital Leadership
- Data-Driven Innovation and the Data Innovation Ecosystem
- Designing Data Products and Services
- Fundamental Data Engineering for Data Scientists
- Data Analytics for Data Scientists
- Scale-up! Working with Really Big Data
- Advanced Analytics for Unstructured Data
- Managing Data Projects and Professional Communication Skills
- Domaine Experience – Real-Life Data Science in Action
- Master’s Thesis (incl. Preliminary Study)
Course structure and modules: Flexibility in creating your profile
The concept of "applied" is at the heart of our programme, and we therefore provide students with the technical, methodological, analytical and communication skills – including the application of Artificial Intelligence – and knowledge they need when working on real-life projects.
Coursework
The Master's degree in Applied Information and Data Science requires students to earn 120 credits under the European Credit Transfer System (ECTS). At Lucerne University of Applied Sciences and Arts, a credit generally equals 30 hours of coursework, which includes attending classes, studying individually, writing term papers and taking exams.
Language of instruction
Teaching language is English, there are only a few German-language modules. However, students are allowed to take the module exam in either German or English, regardless of the module’s language of instruction.
Teaching format
Starting in the autumn semester of 2021, classes will alternate between on-site and online teaching. On-site classes will be held in fixed semester weeks and allow students and lecturers to exchange. In the remaining semester weeks, all teaching will take place online.
Preparatory modules
The first semester includes introductory courses on the important basic principles of applied data science, such as computer science, Python, statistics and experimental design. Students without a documented background in these areas must complete the respective preparatory modules, which count as part of the coursework.
Required modules
In principle, students must complete the required modules for their field; however, exemptions may be granted for those who can document having completed such coursework previously.
Core elective modules
Students must choose a certain number of core electives from a prescribed set of topics. These modules then enable them to create an individual profile.
Master’s Thesis
By completing the Master’s Thesis, students demonstrate their ability to manage a real-life data project by doing thorough research and meeting high professional standards. The programme encourages and supports students in working closely with industry partners, and the Master's Thesis (incl. preliminary study) therefore is an integral part of the programme.
Earn up to 120 ECTS credits with flexible modules
The Master’s programme consists of required modules, including the Master’s Thesis (69 ECTS credits) and core elective modules in three areas (51 ECTS credits). The core elective modules enable students to develop their profile more closely in line with a specific business, technology or analytical area.
What's next?
The course immerses students in challenging specialist and management tasks covering a broad range of functions and industries. It thus also provides an excellent basis for young entrepreneurs looking to start their own business.
We are Data Scientists. What is your superpower?
Our Master's students will learn how to access, integrate, and prepare data from a range of sources and to recognize patterns in complex data sets. Then, they will interpret and use them when making forecasts.
However, their technical and method skills must also match their ability to effectively communicate the insights they gained from the data. Our students, therefore, learn to present the findings they derive from data convincingly and to describe them correctly in accordance with professional standards.
Our Master's program also strongly emphasizes the importance of using such data responsibly and therefore covers in-depth the ethical, legal, and social issues that arise in this connection.