Courses

The course is a fcrash course targeted towards both faculty and PhD students in the humanities and social sciences who are interested in gaining a basic understanding of programming and some practical knowledge on how to use the Python language. During the course you will also learn how to install and work with JupyterLab which is a modern interactive development environment for “literate coding” where you can seamlessly combine written research notes with code, and data. This flexible interface allows users to process workflows in data science, scientific computing, computational journalism, and machine learning – but it is also suitable for data-driven research within the humanities and social sciences.

More about the course.

This course envisions unlocking the future potential digital technology for meaningful heritage practices. The aim is to study the current challenges and implications that may arise to provide actionable knowledge on heritage institutions more generally, but also to potentially inspire the deeper study and implementation of digital methods and tools for historical and cultural inquiry.

The course is offered in partnership with Umeå University. Find out more about the course and how to apply.

The PhD course “Introduction to Cultural Analytics” (7.5 ECTS) is given in autumn 2023 by the Centre for Digital Humanities Uppsala (CDHU) and the Department of ALM. The course has still space available and is open for registration (see below). This course is aimed at PhD students in the humanities and social sciences who do not yet possess specific computational or technical skills, but who are interested in learning more for their future thesis work. The course takes place between weeks 39 and 48 at half speed (50%).

The course introduces methods for computational text analysis from a humanities and social sciences perspective. The course consists of the following thematic areas: introduction to cultural analytics and Python, data curation and analysis, data collection (web scraping, APIs, social media), natural language processing and computational text analysis, and machine learning. The course topics are approached through lectures, practical labs, and guest lectures. The main teachers are Karl Berglund, Marie Dubremetz, Matti La Mela, and Victoria Yantseva.

After completing the course, students are expected to have achieved the following knowledge and skills:

• knowledge about computational text analysis methods and their relevance for humanities and social sciences tasks
• knowledge about machine learning and its basic concepts, as well as such methods’ possibilities and limitations
• practical skills to employ computational methods for text analysis by using existing software, and by following and adapting basic programming scripts
• the ability to critically reflect upon the results derived from computational methods (regarding ethical, statistical, and empirical/material-oriented concerns)
• the ability to highlight epistemological concerns regarding computational and statistical methods from a humanities and social sciences perspective

If you are interested in taking the course or would like to have more information, please contact the course coordinator Matti La Mela (matti.lamela@abm.uu.se).

The last day of registration is Friday 25 August 2023. Please include in your registration email: a description of your PhD topic and a brief motivation why you would like to take the course, a note of approval by your supervisor(s).

Autumn 2023

• Introduction to Cultural Analytics

Spring 2023

• Reconstructing/deconstructing cultural heritage

Autumn 2022

• Introduction to Cultural Analytics Pdf, 94 kB.
• Python for Beginners Pdf, 106 kB.