Data Science

The Master’s degree in Data Science at Technische Hochschule Ingolstadt is designed to equip students with advanced knowledge and practical skills essential for navigating the expanding field of data analytics. This program covers a wide range of topics from statistical methods and machine learning to data engineering and big data technologies. The rigorous curriculum encourages students to engage with real-world data challenges and fosters a hands-on approach to problem-solving.

Structured over four semesters, this Master's program consists of various modules that contribute to a total of 120 ECTS credits. Students undertake a combination of theoretical study and practical application, culminating in a thesis that allows them to explore a specific area of interest within data science. Being a university of applied sciences, Technische Hochschule Ingolstadt emphasizes practical learning, requiring students to complete an internship or practical semester that enhances their professional experience.

This program is ideal for individuals who possess a strong background in computer science, mathematics, or related fields, and are eager to delve into the complexities of data analysis. Through coursework, project work, and collaboration with industry partners, students develop essential skills such as programming, data interpretation, and critical thinking, preparing them for successful careers in various sectors.

Located in the heart of Bavaria, the university benefits from its proximity to numerous Mittelstand companies and technology firms, providing excellent networking and employment opportunities. Additionally, international students can take advantage of the 18-month post-study job-seeking permit, allowing them to explore career options in the vibrant German job market while studying in an English-taught program.

• Data Scientist
• Data Analyst
• Machine Learning Engineer
• Business Intelligence Developer
• Data Engineer
• Statistician

This degree prepares graduates for roles in various industries including technology, finance, healthcare, automotive, and manufacturing, where they can apply their data science expertise to drive decision-making and innovation.