Universität Wien

070158 UE Methodological course - Introduction to DH: Tools and Techniques (2022S)

5.00 ECTS (2.00 SWS), SPL 7 - Geschichte
Continuous assessment of course work
REMOTE

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 25 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 02.03. 15:00 - 16:30 Digital
  • Wednesday 09.03. 15:00 - 16:30 Digital
  • Wednesday 16.03. 15:00 - 16:30 Digital
  • Wednesday 23.03. 15:00 - 16:30 Digital
  • Wednesday 30.03. 15:00 - 16:30 Digital
  • Wednesday 06.04. 15:00 - 16:30 Digital
  • Wednesday 27.04. 15:00 - 16:30 Digital
  • Wednesday 04.05. 15:00 - 16:30 Digital
  • Wednesday 11.05. 15:00 - 16:30 Digital
  • Wednesday 18.05. 15:00 - 16:30 Digital
  • Wednesday 25.05. 15:00 - 16:30 Digital
  • Wednesday 01.06. 15:00 - 16:30 Digital
  • Wednesday 08.06. 15:00 - 16:30 Digital
  • Wednesday 15.06. 15:00 - 16:30 Digital
  • Wednesday 22.06. 15:00 - 16:30 Digital
  • Wednesday 29.06. 15:00 - 16:30 Digital

Information

Aims, contents and method of the course

Course Description:
This course introduces students to common digital tools and techniques used in academic research and in particular the digital humanities. Students will learn approaches to common humanities data problems in the areas of textual data, historic person data, object data/material items, and spatial data. The course will also cover the following key topics: collection and construction of data, data tidying, analytical and research workflows, text analysis, data visualization, mapping, and social network analysis.
During the course students will be introduced to Python, one of the most prominent programming languages in the humanities and data science. The course will explore the use of Python in digital humanities research and projects. Learning Python is supported by DataCamp and students will receive an academic license for DataCamp for the duration of the semester. In addition to the required Python tutorials, students are free to explore the wide catalogue of data analytics and data science courses offered by DataCamp.
Learning Outcomes:
After completing the course students will have gained: intermediate fluency in the Python coding language and its application in digital humanities research, an introductory knowledge of key DH techniques and approaches, an understanding of humanities data, a thorough understanding of how to handle humanities data from the stage of data collection to visualization and analysis.

Assessment and permitted materials

Assessment will be graded based on completion of DataCamp tutorials (10%), homework assignments (60%), and a final project (30%).

Minimum requirements and assessment criteria

This is an introductory course so no prior experience with the tools and techniques discussed is expected.

Examination topics

There is no final examination.

Reading list


Association in the course directory

SP Digital Humanities
DH-S I

Last modified: Th 11.05.2023 11:27