The digital method of the month meeting is a safe space to freely discuss the practicalities of learning and implementing a new digital skill in your research. A big part of conveying research results hinges on how these results are presented. Join us to discuss the main principles of effective and reproducible data visualisation.
The digital method of the month meeting is a safe space to freely discuss the practicalities of learning and implementing a new digital skill in your research. A big part of conveying research results hinges on how these results are presented. Join us to discuss the main principles of effective and reproducible data visualisation.
This lesson teaches how to create a digital gazetteer from a historical text using the Linked Places Delimited (LP-TSV) format. A gazetteer records place names, spatial extents, and historical data, offering a structured knowledge system to connect places, events, and people across time. It is a key tool for spatial history and digital humanities.
This workshop aims to introduce the main strategies of prompt engineering including tips and certain practices to achieve optimal outputs with Generative AI (Gen-AI) tools. After providing a hands-on overview of prompt engineering, certain features of ChatGPT will be discussed for fostering the research practices.
The digital method of the month meeting is a safe space to freely discuss the practicalities of learning and implementing a new digital skill in your research. During this session we will discuss trade-offs regarding gains in productivity and the dangers of producing executable code; how the development of these tools changes the nature of learning to code; as well as best practices and strategies for exploring this safely.
The digital method of the month meeting is a safe space to freely discuss the practicalities of learning and implementing a new digital skill in your research. During this session, we will introduce the concept of Large Language Models (LLMs), discuss their strengths and weaknesses, and explore how they can be effectively integrated into research workflows.
The digital method of the month meeting is a safe space to freely discuss the practicalities of learning and implementing a new digital skill in your research. The method of this month is GIS, or Geographic Information Systems. GIS is a computer system that combines maps and databases to help people create, manage, and analyse information about places.
This course will introduce attendees to the basic concepts and features of Python programming language. The goal is for participants to feel comfortable with creating simple Python programs and provide them with the autonomy and confidence required to progress independently.
This course is an introduction to extracting text from images and scanned PDFs using Optical Character Recognition (OCR) techniques. In the course, we will give you an overview of text extraction, demonstrate how OCR works in practice, using free, ready-to-use tools that are widely available.
This beginner-friendly course will focus on developing skills and a fundamental understanding of R and RStudio. Participants will develop a familiarity with the principles and functionalities of R and RStudio, allowing them to confidently apply these, or indeed seek out new concepts, for their current and future research.
This three-session course introduces attendees to Gephi, a free and open-source network analysis and visualisation tool. The main focus will be on social network analysis, and attendees will have the opportunity to apply their own dataset in Gephi.
Edinburgh Futures Institute (EFI) building, The University of Edinburgh, 1 Lauriston Place, Edinburgh, EH3 9EF
*Deliveries via West Entrance on Nightingale Way.
Email: efi@ed.ac.uk
The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336, VAT Registration Number GB 592 9507 00, and is acknowledged by the UK authorities as a “Recognised body” which has been granted degree awarding powers.
Unless explicitly stated otherwise, all material is copyright © The University of Edinburgh 2021.