FAQ – Frequently asked questions Master of Science in Applied Data Science and AI

During the programme, you will learn about the potential that data and artificial intelligence (AI) harbour in the context of business and society, as well as about their specific applications.

You will also learn how to analyse large data volumes, arrive at meaningful findings and communicate them clearly. At the same time, you will learn how to design data-driven solutions and apply them for a specific purpose.

The programme particularly focuses on:
• Understanding how technology, analysis and management connect
• Developing data-driven products and business models, implementing them technically, and then integrating them into a business environment
• Using data and AI responsibly

Learn more about our students' specific projects and research in their testimonials here.

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The term "applied" here means keeping a consistent focus on how a technology will actually be used.

You will learn not only about the methods and technologies but also how to apply them directly in real-life projects, with the aim of developing data solutions that directly add value for a specific purpose.

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The programme is part of the Business School because data science generally addresses questions relating to business decisions and issues concerning society.
The focus is not on studying data per se but on understanding its role when making decisions, developing business models and managing organisations.

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Data science primarily means analysing and interpreting data in order to identify patterns and make predictions.

Artificial intelligence takes this a step further by including systems that independently make decisions or interact with their environment. Furthermore, machine learning forms an important link between data science and artificial intelligence, both of which the programme covers in great detail.

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AI is an integral part of the programme. You will learn about the methods used in connection with AI and how to apply them appropriately and reflect on them critically.

The programme not only covers ways of implementing AI technically but also teaches you how to apply it appropriately within organisations and when making decisions.

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The programme teaches you about the technologies and tools used most frequently in data analysis and data science today.

Depending on the module, this includes programming languages, analysis tools, visualisation programmes, as well as platforms for processing and managing data.

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The topics for Master's theses are often developed in collaboration with companies or in response to specific questions taken from a wide range of industrial contexts.

The topics range from data-driven analyses to model development, all the way to strategy questions relating to data and AI. Students also work on topics relevant to society and public policy (e.g. sustainability, sport, culture).

Learn more about our testimonials and discussions on Master's theses here.

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Project-based learning is an important programme component for which you can earn ECTS credits. You will tackle real-life problems provided by companies and organisations and work directly on-site with their employees and your fellow students.

The projects are carried out in teams and supported by lecturers acting as learning coaches. You will thus learn to combine theory with practice directly and at the same time build your own project portfolio.

Project-based learning takes place in conjunction with our partner bydo. 

Learn more about project-based learning here.

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Participation is a part of your studies, and information about the available projects and their organisers is provided during the programme.

The programme coordinators will gladly help you with making a choice and answer questions concerning credits.

Learn more about project-based learning here.

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The Master in Applied Data Science and AI programme has students from very different backgrounds – all of whom share a strong interest in data-driven topics.

Students typically

• are around 29 years old on average when they start, 
• have approximately 5–7 years of professional experience and
• work while studying (around 95% of students are employed).

The student body is international and includes people from a wide range of disciplines.

Learn more about the different profiles from the testimonials here.

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Career changers are individuals who do not have a typical background in computer science, statistics or data science. The programme is deliberately aimed at students from a range of disciplines – including business, social sciences, engineering and the humanities.

The programme offers them the opportunity to transition into a new professional field and supports them in systematically building new skills for working in a data-driven environment.

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The programme is structured so that students without in-depth prior knowledge can succeed right from the start, and it deliberately accommodates their differences at the entry level.

Students need to be willing to actively tackle new topics, such as programming or statistics, especially at the beginning. Experience has shown that motivated and interested career changers generally settle in well and successfully develop into data scientists.

Learn more about the projects and profiles of career changers on our page with interviews, research projects and findings.

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You will receive specific support as you get started. The programme has integrated foundation courses that systematically fill in possible knowledge you may have.

In addition, you benefit from:

• Preparatory material for an easy start
• Personal support from lecturers
• Close exchange with fellow students
• Clearly structured course materials
• Hands-on projects in which you apply what you've learned directly

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The programme considers students to specialists if they already have solid knowledge in computer science, statistics, data analytics and similar disciplines.

Such students often have practical experience in working with data and wish to develop their skills further in a specific direction.

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The programme is deliberately designed to be challenging for specialist, in that it not only deepens their knowledge but also prepares them for the next career step.

They will build their profile beyond purely technical aspects and learn to assume demanding specialist and leadership roles – like other graduates, who work in senior, lead, or strategic positions.

The focus is particularly on:

• Applying data science and AI in a business context 
• Understanding how technology, business and communication connect
• Working on complex real-life problems 
• Developing your own project portfolio 

Learn more about the projects and profiles of people who have changed careers on our page featuring interviews, research projects and findings.

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Having a Bachelor's degree is a prerequisite. In addition, analytical thinking, an interest in data, and the willingness to engage with new methods and technologies are particularly important.

Learn more about the detailed admission requirements here. 

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You will find the application deadlines on our website. We recommend that you apply early, as the application process involves several steps.

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The application process consists of the following steps:

1. Online application
2. Self-assessment
3. English language test
4. Personal interview if required 

All steps aim to gauge your background accurately and give you the best possible start in the programme.

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The self-assessment gauges your basic ability to analyse and apply methods and helps you and the programme coordinators to understand where you currently stand.

It does not focus on subject-specific knowledge, but rather tests logical and analytical skills that are important for succeeding in the programme. No preparation is required and no aids or sample tests are provided.

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The English test ensures that you have the required language level to do the coursework (entry level according to the European Framework is C1, with conditions B2). It may include different formats such as reading comprehension, writing tasks, or multiple-choice questions.

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An interview is required if learning more about your profile makes sense – for example, when your prior education or professional background is unclear.

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No. Our students have a wide range of life and professional experiences, which actively contribute to the quality of the learning environment.

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There are no prerequisites for specific programming languages. Although having a basic knowledge is helpful, you can also develop that during the programme; for example, within compulsory modules (statistics, computer science) in the first semester.

Learn more about the modules here.

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Professional experience is of advantage but not mandatory. Many students have several years of experience in a particular field beyond their studies, which enriches the learning experience.

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Data science and AI are interdisciplinary topics that are becoming increasingly important across many disciplines and professions, and the Master's programme therefore has an open access policy. Students thus have a wide range of level skills in IT and statistics, and the programme is geared to the entry skills typically found in graduates with a Bachelor's degree in business administration from a Swiss university or university of applied sciences. Students without relevant prior knowledge must be willing to acquire the basics during the first semester, and corresponding offers are integrated into the programme.

Learn more about the modules here.

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The Master in Applied Data Science and AI programme promotes immersive learning in the fields where data scientists usually work. Students may thus be eligible for a limited number of credits for work they have done previously in a data-related professional field if they can document that such work is sufficiently related to the content of the course. The programme coordinators decide on which professional experience will be recognised.

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Previous coursework completed in specialised Bachelor programmes can be recognised (max. 12 ECTS) in the compulsory modules on request. Recognition of previous coursework completed in Master's programmes is also possible, but limited to the compulsory subjects of the programme.

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The programme enables students to attend modules with external partners (e.g. Global School of Empirical Research Methods (GSERM) at the University of St. Gallen, specific modules at the University of Lucerne, certificate courses at SAS, etc.). Other offers are currently under review.

Such coursework can be recognised as part of elective modules. If you have questions, we recommend that you contact the programme coordinators in advance about having coursework recognised.

Learn more about all the modules on this page.

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The programme is taught by lecturers who work at the university and in the applied fields, most of whom have extensive industry experience, in addition to their academic qualifications.

You will thus benefit from a combined effect of a solid theoretical foundation and direct relevance to the applied fields. The course contents address the challenges that companies, organisations and societies face today.

Learn more about all lecturers here. 

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The programme administrators will gladly help you with practical questions relating to your studies.

• Phone: +41 41 228 41 30
• Email: master.ids@hslu.ch

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You can expect to receive personal and straightforward support during the programme. You will benefit from direct contact with your lecturers and from an active student community.

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The duration of the programme is flexible, and you can adapt the course load to your personal and professional situation. In other words, you decide how long you will be in the programme.

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The maximum duration of study is eight semesters.

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Courses run for 14 weeks and are divided into two seven-week blocks, followed by exams.

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Classes take place on

• Thursday 
• Friday 

This schedule is intended to help you plan your hours where you work.

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A day in the programme can include up to ten lessons (three blocks between 08:15 and 17:55). The exact schedule depends on the module.

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The programme combines a number of formats, with a generally flexible mix of online and on-site components.

Typically:

• approx. 60% online teaching
• approx. 40% on-site teaching

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On-site sessions take place at the Lucerne School of Business, in particular at the Zentralstrasse (Z9) location and near Lucerne railway station (Perron).

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The course gives you some flexibility, as the modules are offered regularly and thus allow you to plan your studies individually.

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Block weeks are individual modules for which you can enrol. They are all electives and are not mandatory for completing the programme.

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Requirements vary depending on the module. In general, active participation is expected, particularly in the interactive formats and projects.

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Generally not. However, on-site sessions may be live-streamed.

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Courses are held on two fixed days per week. In addition, you should plan time for self-study and for doing the exercises and project work.

For the minimum duration of study, the additional workload is approximately 20 hours per week. However, the actual workload depends strongly on your individual background and learning pace.

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If you extend the duration of study, the total workload is distributed across more semesters. However, the teaching days generally remain the same, which means you will need to be on-site for two days per week.

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Many students also work while studying, whereby they can adjust their workload to their individual situation.

As two fixed days of coursework are scheduled and additional time for self-study is required, it is recommended that you plan your workload realistically. If in doubt, a personal consultation may be useful.

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The courses are held in English.

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English at the C1 Level is required. In some cases, students with English at the B2 Level can join the programme by agreeing to certain conditions.

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German language skills are not required.

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Assessments can generally be completed in German or English.

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Assessments involve not only traditional exams but also project work, group work and oral formats.

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Assessments generally take place on-site.

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A degree in applied data science opens up a wide range of career paths for you, as data and AI now play a central role in virtually any industry.

Typical fields include:

• Data science and analytics 
• Machine learning and AI 
• Consulting and strategy 
• Product and business model development

Graduates also qualify for specialised expert roles and positions with leadership responsibilities. Learn more about the possible fields in our professional portraits. 

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Graduates work, for example, as:

• Data scientist 
• Machine learning engineer 
• Data science consultant 
• AI consultant 
• Analytics lead 
• Data and AI strategist 
• Chief digital officer 
• Solutions architect 
• Decision scientist 
• Data analyst 

Many graduates move on into senior or lead positions over the course of their careers. Learn more about these roles in our professional portraits.

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Our Master's programme also prepares you for an academic career, an opportunity that a number of students seize in order to get their doctoral degree.

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Demand for professionals in the fields of data science and AI is very high and continues to grow.

Companies and organisations increasingly require individuals who are able not only to analyse data but also to apply it when making decisions and developing innovations.

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Figures vary significantly depending on the industry and level. The starting salaries of our graduates are approximately 20% above the median annual salary of HSLU Business graduates of CHF 100,000 one year after graduation.

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Data science and AI continue to evolve and are among the key skills required for the digital transformation. The focus is increasingly shifting away from the purely technical side and moving towards strategic thinking, applications and policy.

Profiles that combine technical expertise with domain knowledge and communication skills are particularly in demand.

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AI will not replace data science but rather develop it further. Many technical tasks are supported or automated by AI. At the same time, skills beyond pure modelling are becoming increasingly important, such as:

• Critical thinking 
• Contextual understanding 
• Strategic positioning 
• Communication of results 

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Yes. The programme offers many opportunities to network with companies, in particular through:

• Applied projects 
• Collaboration with partner organisations 
• Exchange with lecturers from industry 
• Access to job postings 

Many students already establish valuable contacts during their studies. Learn more about partnerships and networks on this page.

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The programme combines academic rigour with a consistent focus on the applied fields.

Key characteristics include:

• Individual planning of the studies
• Interdisciplinary access for different backgrounds 
• Learning that is integrated into the actual projects of companies and organisations 
• Close support and an active community 

Many students have a clear goal in mind: to develop their career by pursuing the long-term relevance of data and AI.

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The Master's programme includes components that give you a solid basis in computer science and statistics. Students with documented prior knowledge in these areas can get credit for it. Unlike other programmes, our Master's programme does not require discipline-specific prior studies, and all applicants with a background in the social or natural sciences or the humanities will be considered. Finally, the programme places strong emphasis on the Master's thesis, which can often be combined with professional work or an internship.

This results in a broad competence profile that prepares you for a job or for further studies, including a doctoral degree. Learn more about our courses and modules. 

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An exchange semester is possible. Lucerne University of Applied Sciences and Arts has a large network of international partners. A stay abroad is generally recommended from the third semester onwards.

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The International Office supports you in planning and organising your stay.

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The current tuition fees are shown on our website.

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Depending on your situation, various support options are available, such as scholarships or cantonal funding programmes. HSLU itself does not award scholarships. 

Learn more about scholarships and awards here. 

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Students can benefit from various services, including:

• Discounted meals 
• Sports programmes 
• Access to software and infrastructure 
• Childcare services 

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The programme provides you with state-of-the-art facilities and digital tools, including learning platforms, software solutions, and access to relevant data and analytics environments.

Learn more about the offers available for campus life on this page.

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The student body is international and interdisciplinary, with a wide range of academic backgrounds in business, technology, social sciences and natural sciences, among others. This diversity is a key component of the learning environment.

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Lucerne offers a high quality of life and ideal conditions for studying. The city combines a central location with excellent accessibility and an attractive setting between the Lake of Lucerne and the mountains. The campus is very easily accessible for commuters due to its proximity to the railway station.

Learn more about student life in Lucerne. 

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Lucerne University of Applied Sciences and Arts supports students with families through various services that include:

• Flexible course schedules 
• Information about family allowances 
• Childcare on campus 
• Option to take semesters off

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The university offers an active campus life and various support services. The Student Council organises events, promotes contact among students, and contributes to a vibrant campus. At the same time, the programme's flexible design enables students to optimally balance their studies, work and leisure activities.

Learn more about it here. 

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