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.
Sentiment analysis is the process of determining whether a piece of writing is positive, negative or neutral. Its use has become relatively widespread, including being used to analyse customer feedback, social media, user surveys, and more. This workshop will cover how it works; pros and cons; using it on text, user feedback and online sources.
This workshop will focus on developing practical skills for summarising and exploring data using R or Python. The session will introduce key concepts in descriptive statistics, including measures of central tendency, measures of variability and data distributions.
This workshop introduces the fundamentals of scraping user-generated content from the web using R or Python. The session will be hands-on, working through the process of scraping a selected static website step by step, before concluding with a discussion of the limitations of scraping and the challenges posed by more complex dynamic sites.
This workshop will introduce you to the framework of null hypothesis testing, a simple test of mean differences (t-test), p-values, what they really mean and how to adopt them in your research.
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.
In this course we will cover what application programming interface (API)s are, what they do, how to use them to access and connect data sources. We will also discuss practical considerations such as rate limits, authentication, and the availability of APIs for researchers.
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
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