2024/25 autumn semester digital humanities elective module courses in English

The course introduces the basic notions and typical research questions of digital humanitties as well as the methods and tools to solve them.
The course is taught by visiting lecturers of digital humanitites. The content of the course varies, depending on the lecturer.

The course for fall semester 2020/2021 and also for the fall semester 2021/2022 provides an overview of ways in which humanities scholars can use their computers to work with their data that go beyond simply word processing. We will look at a wide range of topics in order to provide a general introduction into what is possible and to expose students to these topics, so that they can then focus on those aspects relevant to their own research later on.

The course is supported by the (European Union) European Regional Development Fund (University of Tartu ASTRA project PER ASPERA).
Technological advances in computational methods should be accessible to humanities researchers, not only to the hard sciences and tech start-ups.

Algorithms and programs. Representations of algorithms, flow-charts. Branching algorithms. Loops. Sub-algorithms. Developing algorithms for given text-based problems. Program structure. Names. Variables. Operations. Expressions. Boolean expressions, comparisons. Conditional statements. Loop statements. Lists. Functions. User input. Reading from a file. Writing to a file. Simple user interface.

Reelika Suviste, Svetlana Golovko, Merilin Säde, Mark Muhhin, Priit Paluoja, Kristiina Keps

Algorithms and programs. Representations of algorithms, flow-charts. Branching algorithms. Loops. Sub-algorithm. Refining algorithms for given text-based problems. Number systems. Bit, byte. Types. Program structure. Names. Variables. Operations. Expressions. Text output. Boolean expressions, comparing. Methods, description, return of value, invoke. Conditional statement. Loop statement. One-dimensional arrays. Array scan. Array return. Nested loops. String processing. Input and output. Data exchange with files. Screen graphics. Overview of different programming languages. Main phases of software development.

Reelika Suviste, Svetlana Golovko, Merilin Säde, Priit Paluoja, Kristiina Keps

Digital environment rapidly changed the traditional framework in the studies of culture and literature. It could be new ways of storing and representing cultural data or understanding the nature of a digital document; an automated text analysis or computer modeling of complex cultural systems under the emerging data-sensitive theories (as the theory of cultural evolution). No doubt the "digital" became a new norm with blurry borders & elusive definition.
The course is planned to provide students with a roadmap in this essentially trans-disciplinary world, that jumps between editorial theories, geographic information systems, computational linguistics, media studies and network science. Far from being exhaustive, this course will overview major fields, approaches and ideas in DH while paying slightly more attention to historical cultural data & text analysis.

"Methods of extracting keywords and topics from text collections" (Maciej Eder)

The workshop will offer an introduction to information extraction methods from collections of written texts.

DIGIHUM Talk: Andra Siibak

"From artificial intelligence to artificial stupidity. Mapping the dominant enthusiasms and concerns related to the use of AI technologies in education"
students in library smiling

ReproducibiliTea journal club