Data Science – Duales Studium ohne NC: alle NC-freien Studiengänge (2026/27)

Dual studies in Data Science combine rigorous academic training in statistics, machine learning, data engineering, mathematical modeling, programming, and data visualization with paid practical experience in companies where the ability to extract meaningful insight from complex, messy, and large-scale datasets has become one of the most strategically valuable organizational capabilities — placing you inside real data environments from the very beginning of your studies and ensuring that analytical foundations are continuously tested against the practical realities of how data is actually collected, stored, cleaned, interrogated, and translated into decisions that affect products, operations, customers, and strategy. You'll develop both the mathematical depth to understand the methods you apply and the engineering pragmatism to make them work in production — learning to build data pipelines, design experiments, train and evaluate predictive models, communicate findings to non-technical audiences, and navigate the organizational and ethical dimensions of working with data at scale, developing the kind of end-to-end fluency that distinguishes data scientists who can deliver genuine value from those who perform well only in controlled analytical environments. Germany's exceptionally broad industrial and commercial landscape — spanning automotive and manufacturing giants with vast operational datasets, a growing fintech and e-commerce sector, pharmaceutical and healthcare organizations investing heavily in data-driven research, and a technology industry expanding rapidly across every region of the country — creates an environment where dual data science students gain practical exposure across an unusually diverse range of data problems, organizational contexts, and analytical challenges, building a professional profile that reflects genuine industry depth alongside strong academic foundations.