Postgraduate Course: Data / Futures 1 (fusion online) (EFIE11370)
Course Outline
| School | Edinburgh Futures Institute |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
| Course type | Online Distance Learning |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | Please Note:
This course is currently under development. As such, some information may change in advance of its delivery in the 2025/6 academic session.
'Data / Futures 1' provides you with a grounding in interdisciplinary approaches to complex global challenges, combined with introductory skills in working with data and data ethics. It is organised around practical case studies across the arts, humanities and sciences, exploring applications of interdisciplinarity and supporting you to understand the profound influence of data practices in shaping our past, present and futures. You will be introduced to the fundamentals of data ethics, and gain basic skills in coding. You will be able to develop your learning further in the follow-up course 'Data / Futures 2'. |
| Course description |
'Data / Futures 1' will introduce you to the nature of interdisciplinary knowledge, and the societal impact of data practices. It will explore the ways in which interdisciplinary perspectives and diverse ways of knowing can help us address critical global challenges.
You will be supported to build your understanding of the profound influence of data practices in shaping our past, present and futures, gaining a basic knowledge of the data lifecycle, data visualisation and coding in Python. This work will be underpinned by an introduction to the fundamentals of data ethics which you will take forward into the second core course ('Data / Futures 2') and your final project.
The course covers critical themes which will underpin your studies within your programme, introducing you to key literatures and practical case studies of interdisciplinary work across the arts, humanities and sciences. It will provide you with the core skills you will need to apply data-informed methods in a critical way, including an introduction to statistical concepts, modelling and data analysis. The foundations of data ethics and the politics of data will be woven through this work.
As a compulsory course for all EFI Masters students, you will have the opportunity to learn alongside a large and diverse group of people drawn from all programme areas. Taught in the EFI fusion style, you will learn through a combination of methods including fusion seminars and lectures, independent study and reading, with coding workshops, small group work and online discussion woven throughout.
Edinburgh Futures Institute (EFI) - Online Fusion Course Delivery Information:
The Edinburgh Futures Institute will teach this course in a way that enables online and on-campus students to study together. This approach (our 'fusion' teaching model) offers students flexible and inclusive ways to study, and the ability to choose whether to be on-campus or online at the level of the individual course. It also opens up ways for diverse groups of students to study together regardless of geographical location. To enable this, the course will use technologies to record and live-stream student and staff participation during their teaching and learning activities. Students should note that their interactions may be recorded and live-streamed. There will, however, be options to control whether or not your video and audio are enabled.
As part of your course, you will need access to a personal computing device. Unless otherwise stated activities will be web browser based and as a minimum we recommend a device with a physical keyboard and screen that can access the internet.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
| Not being delivered |
Learning Outcomes
On completion of this course, the student will be able to:
- Critically interrogate diverse approaches to research and knowledge, demonstrating an understanding of the value of interdisciplinary perspectives.
- Demonstrate competence in independent working and group collaboration, showcasing their ability to apply interdisciplinary understandings to complex global challenges.
- Demonstrate their ability to critically apply their knowledge of the basics of the data cycle, and their developing skills in coding, to questions arising out of specific global challenge areas and aligned datasets.
- Demonstrate the ability to critically reflect on the ethical dimensions of data practices, artefacts and use cases.
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Reading List
Indicative Reading List:
D'Ignazio, C, and Klein, L.F. (2020) Data Feminism, Cambridge, Massachusetts: MIT Press (chapter 1).
Downey, Allen B. (2024) Think Python (3rd edition). Green Tea Press.
Feng, A. and Wu, S. (2019) The Myth of the Impartial Machine. Parametric Press.
Frodeman, R. (ed.) (2017) The Oxford Handbook of Interdisciplinarity. Oxford: Oxford University Press.
Gidley, Jennifer M. (2017) The Future: a very short introduction. Oxford: Oxford University Press.
Muller, A.C. and Guido, S. (2016) Introduction to Machine Learning with Python: a guide for data scientists. Sebastopol, CA: O'Reilly Media Inc.
Repko, A. F., Szostak, R. and Phillips Buchberger, M. (eds.) (2020) Introduction to Interdisciplinary Studies. Thousand Oaks: Sage.
Robinson, D.G. (2023) Voices in the Code: a story about people, their values and the algorithm they made. New York: Russell Sage Foundation (chapters 1-2).
Spiegelhalter, D. (2019) The Art of Statistics: learning from data. London: Penguin UK.
Vallor, S. (2018) An Introduction to Data Ethics (online resource).
Warne, R.T. (2021) Statistics for the social sciences: a general linear model approach. Cambridge: Cambridge University Press. |
Additional Information
| Graduate Attributes and Skills |
Mindset:
Students will have the ability to make a positive difference to themselves and to shaping the world around them; they will understand how to work positively and ethically with different approaches to knowledge, contributing to addressing some of the world's most complex challenges.
Skills:
Students will develop skills in research and enquiry enabling them to identify and creatively tackle problems; they will develop personal and intellectual autonomy and be able to critically evaluate ideas, evidence and experiences; they will be skilled communicators able to engage effectively with others. |
| Keywords | Interdisciplinary,Futures,Ethics,Data,PG,Level 11,EFI Shared Core |
Contacts
| Course organiser | |
Course secretary | |
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