This interdisciplinary course provides students with hands-on experience in the core technical and analytical skills of Digital Humanities. Methods that students will explore and apply might include text analysis, spatial mapping, and network visualisation, while also gaining foundational coding skills relevant to humanities research. The course includes training in working with digital archives, metadata standards, and cultural data. Ethical and critical engagement with digital tools and methods is embedded throughout, encouraging students to reflect on the implications of their work and its place within broader scholarly and societal contexts.

1x1hr lecture per week over 10 weeks

1x2hr workshop or lab per week over 10 weeks  

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The standard assessments for this course are:

■ Group Project Output and technical commentary - 60%

■ 1500-2000 Individual Critical Reflection - 40%

If required, for instance where a disability prevents a student from undertaking a specific method of assessment, the following alternatives are available:

■ There is no alternative to the project, but flexible deadlines can be offered as reasonable adjustments (students should follow the usual process for extensions)

■ There is no alternative to the reflection, but flexible deadlines can be offered as reasonable adjustments (students should follow the usual process for extensions)

Further reasonable adjustments may be provided where necessary. Students are encouraged to consult with the course convenor.

This course aims to:

■ Develop students' practical digital skills, including basic coding and data manipulation 

■ Support the critical application of digital tools in humanities research.

■ Foster interdisciplinary collaboration and ethical engagement with digital tools and data.

By the end of this course students will be able to:

■ Critically evaluate digital methods in relation to humanities research questions and disciplinary contexts.

■ Analyse the theoretical, interdisciplinary, and critical debates shaping digital humanities practice.

■ Apply and adapt digital tools (e.g. for text analysis, spatial mapping, or network visualisation) to complex humanities data.

■ Write and modify basic code (e.g. in Python or JavaScript) to support data analysis or digital content creation.

■ Evaluate the methodological and ethical implications of digital research practices.

■ Reflect critically on the learning process and communicate digital project outcomes clearly to academic and non-academic audiences