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We want to grow capacity for data-driven and applied digital research across the disciplines.  Our training programme is central to our ambitions and is delivered by researchers and for researchers: it ranges from introductory courses on coding to hands-on classes and monthly deep-dives into a vast range of digital methods. Our training events are open to both staff and postgraduate students.

The world of digital research methods can offer overwhelming possibilities, so with the help of researchers that have already implemented digital methods in their own work, CDCS is also building a series of online Training Pathways that will guide beginners through the steps and concepts they need to master new methodologies and signpost related training and support.

We welcome suggestions for training events and pathways: just get in touch and let us know what you’d like to see on our programme.

Keyboard Pathways

Training Pathways

Unsure where to start with digital methods? 

The world of computational research methods can offer overwhelming possibilities so, with the help of researchers that have already implemented these methods in their own work, we are building a series of pathways that will guide beginners through the steps and concepts they need to master new methodologies.

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Our materials

"Alone we can do so little. Together we can do so much." - Helen Keller, author, disability rights advocate, political activist, and lecturer.

We love sharing.  We make the materials we produce during our training available via Github. They range from markdown help pages to Powerpoint presentations to R and Python notebooks  We encourage people to use this material, and to help us keep the repository up to date by telling us if any of the links or files are not working. 

We also support other open educational resources like The Programming Historian and TEI-By-Example.

Digital Method of the Month

Digital Method of the Month

Each month we hold an introductory session to a different digital research method, and have an honest and practical discussion on what it takes to learn and master it.

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Beyond CDCS

If you are interested in developing your skills, there are lots of options locally and further afield. From online courses to summer schools, our listings will help you identify what is available in the UK and beyond. 

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Data Surgery

Are you using digital methods in your research and struggling to apply what you have learnt to your real-world data?  Do you need some advice and support on how to efficiently adopt data-driven methods for your project?  Book a spot at our Data Surgery!

Our Training Fellows are researchers with digital and data skills. They are able to provide you with advice on how to process your data, how to troubleshoot issues or point you towards more information or training.

Training Programme Sessions

Upcoming Sessions
Past Sessions
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Copyright 101

Autocad Mashup

Digital Drawing with AutoCAD

Machine Learning Mashup

Machine Learning with Python

Machine Learning Mashup

Introduction to Python 

R Logo and code

Introduction to Tidyverse

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Training: Python Library Series

Training Event

Training: Statistics and Visualisation with R

Our Training Fellows

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Lucy Havens

Lucy Havens is based in the School of Informatics where she is researching bias in cultural heritage metadata. Combining natural language processing and data visualization technologies, she seeks to identify and classify bias present in the language of cultural heritage catalogues. She conducts this research through case studies with cultural heritage collections, such as the Archives at the University of Edinburgh.

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Andrew Mclean

Andrew McLean is based in the School of History, Classics and Archaeology. Andrew is an archaeologist with research interests currently focused on the economy of the Roman Adriatic. His methodological approaches include GIS and statistical analysis, particularly expanding on traditional Least Cost Path (LCP) analysis by using circuit theory to model maritime movement. Through this, he is familiar with QGIS, R, Circuitscape, shell scripting and programming languages such as Julia and Python.

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Stefano Bordoni

Since 2017, Stefano has been a PhD candidate in Archaeology. His research explores the potential of medieval Umbria, in central Italy, under the lens of Architectural Archaeology. One of his major research aims is to turn building materials into quantitative data in order to identify patterns. In doing so, IT resources have been essential. In particular, he takes advantage of photogrammetric surveying, AutoCAD vector drawing, QGIS geoprocessing and RStudio data management and visualisation.

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James Besse

James Besse is a PhD student in Science, Technology and Innovation Studies. James’ research is on the implementation of e-ID systems, specifically looking at the EU Settlement Scheme. He uses text mining alongside social surveys and interviews to understand user experience with the EUSS. Broadly, James is interested in the social impacts of new technologies, and how digital methods can help to understand them. He is happy to provide assistance with R, statistics, web scraping, data visualization, and research design.

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Daniel Wheeldon

Daniel has recently completed his Ph.D. in musicology. He worked with museum and private collections in the UK, Germany, and USA  using traditional and digital technologies to extract information from original art objects and then to make working copies. While he was a Chester Dale fellow at the Metropolitan Museum of Art, NY, he participated in a project investigating the efficacy of photogrammetry in studying museum objects. He has training and over ten years of experience making and restoring musical instruments and has an ongoing interest in the intersection of traditional craft with emerging technologies.

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Fang Jackson-Wang

Fang Jackson-Yang is based in the School of Philosophy, Psychology, and Language Sciences. Fang researches how people communicate prominent information in transitive events (e.g., “Jerry kicked the oil lamp”). She uses eye-tracking techniques to investigate when and how listeners make predictions of the endpoints of such events (e.g., the lamp fell on the floor). She also uses laboratory and digital corpus data to investigate how speakers use various sentence structures and other linguistic means to describe such events in different settings and what factors influence their choices.

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Bonan Zhao

Bonan Zhao is a PhD student in cognitive psychology. She studies the twists and turns of how people generalize causal concepts to novel situations. In her research, she builds computational models to simulate human cognition and runs large online experiments to evaluate model predictions with people's judgments. She used to teach programming and web development to refugees in Amsterdam, and has been an enthusiastic advocate of open research practices.

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James Page

James is an archaeologist whose research focuses on the economy of Northern Italy in the Roman period. His work uses a combination of network modelling and statistical analyses to look at the dynamics behind inland trade and test the validity of prior modelling. He is familiar with QGIS, R, and OpenRefine. 

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Bhargavi Ganesh

Bhargavi is a PhD student at the University of Edinburgh, doing interdisciplinary research at the intersection of philosophy, computer science, and public policy. She is affiliated with the Center for Technomoral Futures and the UKRI Research Node on Trustworthy Autonomous Systems Governance and Regulation. She has worked at non-profit research organizations and government institutions, where she studied the impact of housing policies on marginalized groups. In her doctoral research, Bhargavi is developing frameworks to guide the governance and regulation of autonomous systems and decision-making algorithms in various fields including health, robotics, and finance. 

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Pedro Jacobetty

Pedro Jacobetty is a sociologist whose research interests intersect include technology, digital culture, knowledge production and circulation, media and communication. He is also interested in innovative ways of using digital methods for social sciences and art.