This course provides an overview of the main cultural and political challenges in big data and AI, as well as the importance of humanities' contributions. Topics include ethical questions regarding data extraction, discriminatory bias, accountability and transparency, especially concerning automated decision-making processes.
This course teaches you how to conduct data analysis with Python, working with core libraries such as Pandas and Numpy. It introduces computational thinking and provides an overview of programming fundamentals. The course follows a flipped-learning approach, working with reusable code notebooks and regular homework exercises.
This course builds on Computational Thinking and Data Analysis, allowing you to practice your programming skills in group-based activities focused on analysing socio-cultural data. During the project, students engage in data wrangling and exploratory data analysis, sampling and hypothesis testing, data modelling and visualisation as well as best practices in open science.
You can fulfil the elective space through an Embedded Research Project or an annually changing selection of elective courses. The Embedded Research Project takes place within a research institute, cultural heritage organisation, media company or governmental agency. It is a predefined research project, developed in collaboration with selected partner institutions. It leverages existing partnerships with academic, cultural and governmental organisations.
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.
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