Data Science & Artificial Intelligence

Why study Data Science & Artificial Intelligence (DSAI)?

The DS&AI Master’s at TU/e combines advanced engineering, machine learning, and data science to build intelligent, high-impact systems. 

Our programme is the only engineering master’s in the Netherlands that brings together the full depth of both data science and AI. Whether your interests lie in process mining (invented right here at TU/e), visual analytics, machine learning, or knowledge integration, DS&AI gives you the freedom to create your own path. You will be guided by world-leading researchers and embedded in a region known for innovation.

But this program is more than just about technology. With a dedicated focus on AI in context, you’ll learn to recognise ethical, social, and domain-specific challenges and design solutions that are fair, transparent, and sustainable.

As a DS&AI graduate, you won’t just be fluent in Python or know your way around a neural network. You’ll be an engineer who can connect data to meaning, AI to impact, and research to innovation.

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Specializations

Data Science and AI in Context

As an engineer working in data science and artificial intelligence, you will encounter societal, ethical, and domain-specific issues. The courses in this trajectory expose you to these issues and teach you how to address them when designing new solutions.

Data Management and Engineering

Data Management Systems (DMS) provide fundamental, underlying infrastructures to identify and extract value from data for organizations and society. The courses in this trajectory teach you about the foundations, applications, and engineering of next-generation data and knowledge management methods and systems.

Algorithmic Data Analysis

Algorithms play an undeniable role in data science: they enable efficient and automated data handling, analysis, and visualization. In this trajectory, you will learn how to develop algorithmic solutions for high-quality data analyses and for making optimal recommendations in a verifiable and explainable manner. A broad set of algorithmic tools is an essential part of data scientist's repertoire.

Process Mining and Visual Analytics

The actual analysis or (prediction) problem you need to solve is typically unknown at the start of a project, while the solution requires a valid and explainable integration of domain knowledge, data, and models. The courses in this trajectory equip you with the mindset, foundational knowledge, and engineering skills to achieve this with two unique specializations available only at TU/e: Visual Analytics and Process Mining.

Statistics

The statistics track provides rigorous methods and models for summarizing data of various phenomena into understandable features that have a direct impact on and enable the interpretation of real-world situations. The courses in this trajectory teach you a broad range of statistical methods to analyze and model temporal and big data sets, and how statistical methods can be used to learn from this type of data.

Data Mining and Machine Learning

Within Data Mining and Machine Learning, you study the foundations and practical approaches of knowledge extraction from vast collections of complex data. This trajectory focuses on data mining and machine learning approaches and techniques to develop extremely prevalent, end-to-end solutions for algorithmic decision making. You probably already use them multiple times a day without even knowing it!

AI and Machine Learning

This track involves the study of algorithms that improve through experience.The courses involved teach you the main techniques and approaches in modern AI,with an important focus on solutions that are not only accurate but, most of all, efficient, reliable, interpretative, robust, and trustworthy.