Scientific research and teaching is increasingly influenced by computational tools, methods and paradigms. The social sciences are no different, with many new forms of social data only available through computational means (Kitchen, 2014). While to some degree social science research has always been marked by technological approaches, the field of computational social science involves the use of tools, data and methods that require a different skill set and mindset.

The following topics are covered under this training series:

1. Thinking computationally
2. Writing code
3. Computational environments
4. Manipulating structured and unstructured data
5. Reproducibility of the scientific workflow

The training materials - including webinar recordings, slides, and sample Python code - can be found in the following folders:

• code - run and/or download example Python code using our Jupyter notebook resources.
• faq - read through some of the frequently asked questions that are posed during our webinars.
• installation - view instructions for how to download and install Python and other packages necessary for working with new forms of data.
• reading-list - explore further resources including articles, books, online resources and more.
• webinars - watch recordings of our webinars and download the underpinning slides.

We are grateful to UKRI through the Economic and Social Research Council for their generous funding of this training series.

• To access learning materials from the wider New Forms of Data for Social Science Research training series: [Training Materials]
• To keep up to date with upcoming and past training events: [Events]
• To get in contact with feedback, ideas or to seek assistance: [Help]

Thank you and good luck on your journey exploring new forms of data!

Dr Julia Kasmire and Dr Diarmuid McDonnell
UK Data Service
University of Manchester