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Master
Cultural Data & AI
Vergelijk
COURSES SEM 1 SEM 2 SEMESTER 1 SEMESTER 2 EC
  • Critical Perspectives on Data & AI - Concepts and Methods
    Period 1
    12

    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.

  • Cultural Data Analysis - Concepts and Methods
    Period 1
    Period 2
    12

    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.

  • Data Project
    Period 3
    6

    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.

  • Electives or Embedded Research Project
    Period 4
    Period 5
    12

    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.

  • Master's Thesis
    Period 4
    Period 5
    Period 6
    18

    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.

Compulsory course
Elective
Prof. Tobias Blanke
Copyright: UvA
My research focuses on artificial intelligence and big data devices for research Prof. Tobias Blanke, University Professor of Artificial Intelligence and Humanities Profile page Tobias Blanke

Transferring to the Research Master’s Media Studies

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.

Copyright: Paula Helm
The mission of my work is to move AI-Ethics from the PR- to the Engineering- and Development-Level Dr Paula Helm, Asisstant Professor Critical Data Studies and AI Ethics Profile page Dr Paula Helm
Frequently Asked Questions