Master Programme

Hello, Patricia and Donnacha

Meet Dr. Patricia Feubli and Prof. Dr. Donnacha Daly, the new leadership of the MSc in Applied Data Science and AI, in conversation about the programme's qualities, key skills, and what's next.

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

Starting in September 2026, Dr. Patricia Feubli and Prof. Dr. Donnacha Daly have taken over the leadership of the MSc in Applied Data Science and AI. Their first official act was renaming the programme; you can read more about that in our blog post.

With that milestone behind them, the two are now ready to open a new chapter.

Both are familiar faces at HSLU: Patricia has been a lecturer and deputy programme head since 2019, with a research focus on human-centered AI systems, while Donnacha has helped shape HSLU’s AI education as Co-Founder of the Applied AI Center and Head of the Bachelor’s programme in AI & Machine Learning.

3 Questions for the New Programme Heads

We asked them where they see the programme’s unique strengths, and how they look at its future development. Here’s what they had to say:

What strengths does the programme bring that you would like to continue building on?

Patricia: The curriculum is incredibly agile in terms of content. On one hand, we can quickly build new modules to teach new topics. On the other hand, our lecturers work at the forefront of developments and build these directly into the modules.

Our faculty – our lecturers – are outstanding, established experts who have worked for many years as data scientists, (data) engineers, and analysts. We have people from Google DeepMind, IBM, major insurance companies with excellent data science teams, research-strong institutions, and AI startups.

We manage to train even career changers into full-stack data scientists within two years – graduates who go on to succeed in the job market.

Dr. Patricia Feubli

The programme’s management team (and by that I mean all six of us) works with full passion for the programme and keeps driving it forward. We’re not administrators – we’re shapers.

Donnacha: Most of our students are working during their studies, and have many years of work experience. We can therefore leverage their practical knowledge of real world use-cases and business pain-points, to ensure that what they are learning can be brought back into their day-to-day projects and processes, with immediate impact. This is the core strength I would like to build on in the next years: the deeply hands-on and practical nature of our Masters in Applied Data Science and AI.

Which of the skills taught in the programme show up today as particularly valuable among alumni?

Patricia: The ability to ask the right questions. The biggest challenge for a data scientist is sharpening a vague problem statement precisely enough that it can be translated into measurable variables and answered with data and technology. This translation work requires a lot of domain knowledge and data expertise, patience, and the willingness to keep asking questions.

Developing a feel for the data. To tease the necessary information out of the data, you first have to look closely at the data itself – its properties, its structures, its imperfections, its quirks, its big and small patterns – before you can even dive into the analysis. Again and again, we see data scientists jump into data analysis too quickly, heading straight for the “juicy” part of the project. As a result, data exploration often has to be repeated later on, because the data wasn’t looked at properly the first time. That costs time, money, and nerves.

Donnacha: The emphasis on data-literacy, especially for non-technical career changers, is a core value proposition. The ability to source, process, and analyse relevant unstructured datasets for the purpose of creating business insights and capturing previously unseen value is a skillset that will stand to our students long after they graduate.

Explore the MSc in Applied Data Science and AI

What topics and developments will shape the programme in the future?

Patricia: Clearly, developments in the field of artificial intelligence will continue to shape the programme. They influence not only the methods data scientists use, but also how data scientists do their work. What will be delegated to AI in the future? Where is human oversight still needed, and what will a data scientist continue to do without AI support? Which machine learning methods will become the new standards? How deep will programming skills need to be going forward? What new skills will data scientists need to master? These are questions we’ve always asked ourselves, and they will continue to accompany us closely in the future.

Donnacha: The new era of AI has entirely disrupted how many businesses and processes are managed.

We see this as a huge opportunity to provide our students with up-to-date skills e.g. in Generative-AI and Agentic-AI for rapid prototyping, iterative solutioning, and accelerated automation in their data-projects. Our curriculum is fine-tuned on a continuous basis to ensure we are right on the front of these rapid developments.

Prof. Dr. Donnacha Daly

On the other hand, there is a downside to AI which comes with excessive cognitive offloading – humans will essentially default to the easiest route for task completion. For that reason, we see an increased emphasis on critical thinking, design judgement and decision making as important developments in our programme.

Two Perspectives, One Direction

Though their answers come from different vantage points, Patricia and Donnacha converge on much the same convictions: staying close to real practice, keeping a sharp eye on the data, and using AI thoughtfully rather than blindly. It’s this shared outlook that will guide the MSc in Applied Data Science and AI confidently into its next chapter.