This course explores the cultural, political, and ethical challenges of data and AI, emphasising the vital role of media studies and the humanities. You will also examine the societal impact of AI, focusing on issues like power, justice, discrimination and marginalisation.
In this course you will explore key approaches to the cultural, political, and ethical challenges of data and AI. Each week focuses on a distinct method through practical assignments. You will start by engaging with core themes and mapping key trends and institutions in the field. From there, the course explores various methodological approaches.
This course introduces computational thinking and programming fundamentals, with a focus on cultural data analysis and its limitations. It covers Python basics, data structures, algorithmic thinking, and introductory techniques in data analysis, visualisation, and machine learning. You will also explore conceptual and critical perspectives on using data in cultural and social analysis, working with texts, images, and online traces.
This course offers practical training in Python-based programming and cultural data analysis. You will learn to manipulate data, apply statistics, create visualisations, and explore basic machine learning. You will also explore how to apply these skills to real-world cultural datasets, including text, social media, and images.
This course gives you hands-on experience with methods from earlier in the programme through a group project on socio-cultural data. Working in one-week sprints, you’ll apply techniques like data wrangling, modelling, and visualisation. Projects follow an agile framework and can be tailored to your interests. The course also prepares you for your thesis and embedded research project.
This programme offers 12 ECTS in elective space, which you can fulfil through an Embedded Research Project or an annually changing selection of elective courses.
The Cultural Data & AI Master's thesis concludes the programme and involves an independent research project under expert supervision. The Embedded Research Project can provide the basis for the Master’s thesis.
The programme offers 12 ECTS in elective space, which you can fulfil through an Embedded Research Project. This project takes place within a research institute, cultural heritage organisation, media company or governmental agency. It’s a predefined research project, developed in collaboration with selected partner institutions and leverages existing partnerships with academic, cultural and governmental organisations.
My research focuses on artificial intelligence and big data devices for researchProf. Tobias Blanke, University Professor of Artificial Intelligence and Humanities Profile page Tobias Blanke
Students who show exceptional promise during a regular or professional programme are encouraged to continue their studies in a research programme. Once students are admitted to the Media Studies research Master’s programme, they can transfer credits earned during their previous course of study towards their research Master’s degree. The Examinations Board determines which courses qualify for transfer.
Within the Media Studies research Master’s programme, the Cultural Data & AI specialisation focuses on further developing computational and conceptual skills for the critical study of data and AI. This intensive and selective two-year programme has been developed for students with proven ability in and passion for research.
The mission of my work is to move AI-Ethics from the PR- to the Engineering- and Development-LevelDr Paula Helm, Asisstant Professor Critical Data Studies and AI Ethics Profile page Dr Paula Helm
No, there are no possibilities to do an interneship, but you do have the opportunity to do an Embedded Research Project.
Yes, there is a pre-Master’s programme in Media Studies for students who do not fully meet the entry requirements of this Master's programme.
Digital Activism (12 EC)
This course examines how civil engagement, activism, social movements, political participation, and advocacy have changed since the diffusion of the internet. We will work with both real-world case studies and theory to explore activism in the digital age through the lens of technology and technology-enabled collective action.
Social Media and Contemporary Issues (12 EC)
This course explores two methods of analysing and mapping current issues. First, it involves analysing the actors, objects and substance of an issue. Second, it focuses on incorporating the map into the controversy or issue area. The course delves into controversy mapping, risk cartography and contemporary cartography schools, examining their theories and practices.
You will have 3 to 4 classes per week on campus.
No, there are no possibilities to follow classes online.
No, you don’t need previous experience in data sciences.
Check the entry requirements