Data Science & Big Data
|Digital Text Analysis
Digital text is ubiquitous in contemporary society. Modern computational technology enables exciting applications in both research and the industry. In this Master of Digital Text Analysis, you will acquire all critical and computational skills that are nowadays expected of experts in digital text analysis.
The curriculum is unique in its emphasis on data-heavy approaches to language and text from a Humanities perspective. Starting from scratch, the modules cover a wide array of text technologies, ranging:
from artificial intelligence (machine learning)
over data science (statistics)
to natural language processing (computational linguistics)
This ambitious programme seeks to prepare the next generation of highly self-reliant, culture-aware experts in text analytics, who are highly employable in a variety of research contexts across academia and the industry, including the cultural sector.
Starting from scratch, the curriculum covers a wide array of text technologies.
Natural Language Processing: Technologies from computational linguistics are nowadays crucial in digital text analysis. This module offers an extensive introduction to modern pipelines in Natural Language Processing. Jointly, we work towards practical applications on textual data, as well as solutions for the many challenges that remain open in the field.
Data Science: Employers in academia and the industry increasingly expect data scientists to be able to rapidly extract relevant insights from large document collections. In this module, we focus on exploratory data analysis and practical data visualization, involving challenging, real-world datasets.
Machine Learning: Deep learning features prominently in this programme, as a crucial component of contemporary artificial intelligence. Modules focusing on neural networks are supplemented by a wide-ranging and in-depth survey of established, alternative methods from machine learning.
A unique feature of this curriculum is the compulsory programming bootcamp at the beginning of the first semester. This 3-week course makes no assumptions whatsoever about the students’ coding proficiency and will provide a no-nonsense introduction to modern computer programming and the wider scientific ecosystem in computing.