Sage Campus blog
Learning Python can be daunting for social scientists who don’t have a technical background. Dmitrijs Martinovs, assistant at SAGE Campus, tells us his experience of switching from SPSS to Python to better conduct analyses when undertaking a research masters in social policy.
To accompany the launch of our new course on November 26, Introduction to Text Mining for Social Scientists we’ve put together this handy video collection with SAGE Campus course instructor Gabe Ignatow. We’ve broken them down into useful sections to help give you a quick overview of Text Mining; we hope you find them useful. Sign up now for Introduction to Text Mining for Social Scientists.
Online learning done well can remove barriers to learning by offering flexible ways to learn new skills, whenever you want and wherever you are. But creating effective online learning isn’t easy and the challenges are especially pronounced when teaching complex and advanced topics. Read our top tips for designing effective online learning based on our experience of developing SAGE Campus courses.
PhD candidates from the University of Nottingham ESRC Doctoral Program told us about their experience with our Introduction to Python e-learning course.
To accompany the launch of our new course on November 26, Introduction to Text Mining for Social Scientists we’ve put together this handy video collection with SAGE Campus course instructor Gabe Ignatow. We’ve broken them down into useful sections to help give you a quick overview of Text Mining; we hope you find them useful. Sign up now for Introduction to Text Mining for Social Scientists.
All of the information you're going to find here has been extracted from the online course Introduction to Text Mining for Social Scientists. The chosen topics will provide you with a taster of what text mining is and we hope this guide is your first step to learning more about this exciting field.
What is text mining and how is it used in social research?
This guide includes carefully chosen topics that are perfect for people who have no experience of R. Each topic is intended as a taster to introduce you to R, the terminology, and to share useful resources to aid your further adventures with R. We hope this guide is a great starting point for you to learn about R!
Whether your looking to improve the visualisation of your data or master your next programming language we've got you covered. Explore all our free webinars in one place
A fantastic benefit of the course Introduction to Data Science for Social Scientists is that it introduces you to using Jupyter Notebooks, part of the Jupyter Project. But what is Jupyter? And why is it such a useful tool? We asked course instructor Geoff Bacon to share his thoughts.
Watch this webinar and learn how good decision-making leads to effective data visualisation.
At SAGE Campus we’re passionate about providing a learning journey that is successful from start to finish. To ensure that our courses are pedagogically effective and provide an engaging learning experience, we work with an eLearning Advisory Board. Read about how the expert feedback we receive is woven throughout the creation of our courses.
Learn how to perform simple tasks using R with our free training video.
Watch our free webinar and learn more about the role that quantitative text analysis plays for social scientists when working with large amounts of data.
See the value of photo-imagery within a chart display, and how using consistent composition and style enhances visualisations.
Do you want to learn more about how Python can be used for working with social data? Watch our webinar with SAGE Campus course instructor, Rob Mastrodomenico and find out all you need to know.
The projects that are the focus of this post demonstrate clever approaches to axis, and come from the Washington Post, the New York Times and Sports TV coverage
This guest post, written by Professor Ryan Watkins, shares a conceptual framework for preparing PhD students for study, research, and working in data intensive environments powered by intelligent technologies.
This post concerns approaches to annotating charts and includes observations on visualisations on gun crime, the NFL and dialogue analysis of ‘The Office’. They have been created by Andy Kirk, a UK-based data visualisation specialist and course instructor on Introduction to Data Visualisation.
Find out how to make clever choices about label placement, and how labels that appear to be simple, can actually make visualisations confusing.
