Master Programme

Applied Data Science and AI: our Official Renaming

New Name, Established Practice: Why the MSc in Applied Information and Data Science Is Becoming the MSc in Applied Data Science and AI.

As of August 2026, our programme is called MSc in Applied Data Science and AI.

The MSc in Applied Information and Data Science is being renamed to the MSc in Applied Data Science and AI. The new name makes visible, on the outside, what the programme has already been teaching: the full value chain of data and artificial intelligence. In this article, we take a closer look at the background behind that decision.

The initiative to rename the programme came from Dr. Patricia Feubli and Prof. Dr. Donnacha Daly, the programme’s incoming directors. They noticed that while the curriculum had continuously adapted to the shifting technology landscape, the name hadn’t kept up – an inconsistency they felt was hard to justify. A 2025 HSLU study on the Swiss AI labour market backs that observation, underscoring that Swiss industry is looking for experts who can both analyse data and put AI systems to meaningful use:

“When the programme launched in 2018, there was strong demand for experts who could extract insights from data – traditional data scientists. Given the rapid pace of methodological and technological advances since then, the focus today is no longer just on gaining insights from data, but increasingly also on the machine-based solving of cognitive problems – that is, the development and handling of data-driven, autonomous (generative) AI systems.”

Dr. Patricia Feubli

The renaming makes clear that the programme covers the entire data value chain, from data through information and knowledge to intelligence.

From Data Collection to a Strategic Question

“How can companies generate new business models through their data? And what are the consequences of the insights gained from data for companies and for people?”

For Dalith Steiger-Gablinger, Global AI Strategist, Innovator and Advisor, these are the central questions that now sit at the heart of the data scientist profession.

For a long time, companies mainly collected data and considered how to use it to improve existing products and services. A legitimate approach – but one that falls well short of data science’s full potential.

A Topic Education Recognised Early

The education sector had already realized then years ago that this was a very hot topic.”.

replies Prof. Dr. Andreas Brandenberg, founder of the MSc Applied Information and Data Science, picking up her point in their conversation.

30% of all modules in the MSc Applied Information and Data Science have long included AI content.

This shows up, for instance, across numerous research projects. Students Rodrigo González Alonso and Cengiz Cetinkaya, together with Professor Peter Gloor, developed a machine learning model that detects whether a cow is content or distressed.

We spoke with them about their work – read the blog post here.

Not Whether, But How

What matters, however, is not whether artificial intelligence is used – but how. The best LLM is useless if you don’t know which questions to ask. The same is true for data science. Both disciplines exist to solve business and societal problems: data feeds into decision-making processes, business models and organisations, and in some cases forms their very basis. The data science profession, then, cannot sidestep AI.

According to Brandenberg, data scientists are increasingly becoming decision architects who actively shape decision-making processes within companies:

“Today it’s less about building models from the ground up as very loose structures. It’s more about assembling, orchestrating, coordinating and implementing, and evaluating AI subsystems.”

Prof. Dr. Andreas Brandenberg

AI Isn’t for Shortcutting Theses – It’s for Practical Experience

Educational institutions worldwide are grappling with unwanted uses of AI. Our master’s programme is built on a foundation of practical relevance, which makes it all the more important to equip students not only with the skills to apply data science purposefully across corporate value chains, but also with the skills to use AI as a meaningful complement to that work.

85% of our graduates work in a data science or AI-relevant field.

(Source: Internal Alumni Survey 2026, n=68 graduates)

One of them is Tim Giger, CTO Data & AI Consultant at Swisscom: “My job actually covers the full range: from strategy to architecture and solution design, all the way to implementing platforms and solutions in the data and AI field for customers in the Enterprise segment. Specifically, this can involve developing concepts for data architectures and platforms, setting up data warehouses and lakes, implementing ML models, or devising data strategies,” he told us.

Read more about his story in our blog post on his journey.

Explore the MSc in Applied Data Science and AI

A Name That Traces a Development

The new name, then, isn’t a jump onto a trend – it’s the logical label for a development that has long been under way within the programme. Data science and artificial intelligence have belonged together for years; now the programme’s name reflects that too.

“AI technologies have been in development since the 1950s. But their ability to imitate – and in some cases surpass – human performance has only emerged in this past decade. This represents a fundamental shift in business and society, one that won’t disappear again. On the contrary, as it continues to improve, it will become ever more deeply embedded in business operations, and its importance will keep growing.”

Prof. Dr. Donnacha Daly

There’s no shortage of exciting problems ahead – and we look forward to tackling them together with our students.