Course & Training
ATRIUM Summer School 2027: Artificial Intelligence for the Humanities
Offered by LINDAT/CLARIAH-CZ, Charles University / ATRIUM
Location
Prague, Czech Republic
Funding
Fully Funded
Study level
Undergraduate, Master's, Graduates, PhD, Postdoctoral, Researchers, Faculty & Academics
Field of study
Arts & Humanities, Computer Science & IT, Social Sciences, Mathematics & Statistics, Other
Application deadline
November 30, 2026

About This Course and Training
The ATRIUM Summer School 2027 is a two-week academic training programme focused on applying artificial intelligence and computational methods to research in the humanities and social sciences.
The programme will take place at Charles University in Prague from July 12–23, 2027. Participants will explore the foundations of AI while gaining practical experience with data processing, text analysis and computational research methods that can be applied to humanities and social-science research.
The training is designed to move beyond a purely theoretical introduction to AI. Participants will work with research data, use the R programming system, examine AI methods including neural networks and develop practical skills that can be incorporated into their own academic or research projects.
What Participants Will Learn
The programme covers practical and conceptual aspects of computational research, including:
- Foundations of Artificial Intelligence.
- AI applications in humanities and social-science research.
- Text analysis.
- R programming.
- Systematic data processing.
- Statistical analysis.
- Research data and computational methods.
- Introduction to neural networks.
- Technical literature relating to AI.
- Practical application of AI methods to research data.
Participants will be encouraged to consider how these methods can be adapted to research questions in their own disciplines.
Eligibility
The programme is intended for students and researchers interested in applying AI and computational approaches to humanities or social-science research.
Applicants should have:
- Basic proficiency in the R programming system.
- Elementary knowledge of systematic data processing.
- Elementary knowledge of statistical analysis.
- An interest in experimenting with AI and neural-network methods.
- An academic or research interest that can benefit from the training.
This is therefore not designed as a completely beginner-level programming course. Applicants are expected to have some previous experience with R and quantitative or structured data.
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Check the official website for the latest eligibility requirements, application instructions and deadlines.



