CDCS is delighted to announce our Summer School on Text & Data Analysis. The event is free, but places are limited.
The Summer School is an intensive, 5-day, in-person event, with a heavy practical focus. It consists of two simultaneously run streams: A Gentle Introduction to Coding for Data Analysis, and Text and Data Analysis in the Wild. Find out more about each stream and which best suits your needs below.
This course is designed for researchers who are complete beginners with no prior knowledge of coding and data analysis. Through lectures and exercises, attendees will learn how to code in Python, starting from core concepts such as variables and loops, through to coding live data visualisation. The course explores the basics of programming: variables, functions, loops, operating on data structures, data wrangling, visualisation, and publishing to the web. By the end of the course, attendees will understand how to bridge the gap between humans and computers, and how to apply the skills they have learnt to their own data analysis and research. This course is intended to be a foundation for those intending to start a journey towards analysing Humanities and Social Sciences research data.
No previous coding experience is required.
Encourage collaboration with other students to achieve goals and tasks. Instructors will be available in the room to help.
The course combines mini-lectures, guided coding examples and programming challenges.
Students will work towards describing and visualising data.
Provides the foundations needed to continue your coding journey through self-study.
This course is designed to help researchers with coding experience understand how data and text analysis projects are performed in a research environment. It starts with identifying a series of research questions connected to this year’s core topic (cost of living in Scotland and the UK). Then it explores how computational methods can be used to obtain, clean, and analyse structured and unstructured datasets in R to answer those questions. Topics will include web scraping, text analysis, sentiment analysis, data wrangling, statistics, and data visualisation.
General knowledge of the interface of RStudio and coding is required. Materials will be released in advance to support attendees in refreshing their R skills.
Fosters interdisciplinary thinking by bringing social science and humanities researchers together to explore methods.
Covers both structured and unstructured data.
Illustrates the development process of data-led projects by moving through phases of the project lifecycle.
Challenge-led, helping researchers learn how to deal with real-world data.
The course is primarily aimed at researchers from Scottish higher education institutions, with a marked interest in developing their digital and computational skills. We will also consider Scotland-based professionals who are keen to upskill their digital methods.
The hands-on classes offered daily will involve live coding in R and Python.
For Stream 1: A Gentle Introduction to Coding for Humanities and Social Science no previous knowledge of coding is required and the practicals will be delivered in Python.
For Stream 2: Text and Data Analysis in the Wild a general knowledge of the interface of RStudio and coding is required. Materials will be released in advance to support attendees in refreshing their R skills.
This Summer School has is free, but places are limited. In order to be considered, please fill in the Application Form using the link below detailing how attendance will enhance your research/work.
The Summer School is funded by the Centre for Data, Culture & Society, the Edinburgh Futures Institute, the Scottish Graduate School of Social Sciences, and the Scottish Graduate School for Arts and Humanities.
