The University of Exeter Q-Step Centre received funding from the European Social Fund (ESF) to deliver a series of training courses, which sought to develop advanced data analytics skills. These are skills that are becoming increasingly adopted in a wider variety of areas by both small and large organisations.
The SMART Skills project has now ended. We are hoping to secure new funding to resume offering these or similar data analytic courses 2024.
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The courses we delivered over the course of the project included:
1. Critically Interpreting Data - This short course will develop your ability to think critically about data. Using practical, real-world examples, you will examine a range of data uses from creation to communication. By the end of the course, you will feel more confident in your ability to interpret representations of data in daily and academic life.
2. Misinformation in the Modern World - This short course will focus on the different types of information disorder in the modern world (mis-, dis- and mal-information) and how they vary upon the criteria of falseness and intention to harm. By the end of the course, you will understand the historical evolution and dissemination of dis-information, how social science examines conspiracy beliefs, what conspiratorial mentality is and how widespread conspiracist views are in the general population.
3. Essentials in Excel - This course provides the basic foundations for you to understand, execute and communicate data analysis. Over three days, you will gain valuable skills that you can market to employers, gain confidence in your ability to work with data, and create a knowledge base that you can build on for years to come.
4. Introduction to Python - In this introductory course, we'll dive into learning Python from scratch and applying the skills of data analysis to a real-world dataset. In this course, we will touch upon the most crucial skills of working with data, such as exploring and subsetting the dataset, creating new variables, cleaning data, visualizing the distribution of variables, running statistical tests and inferring the relationship between two or more variables. At the end of the course, you will have the time to work on a group project on the topic of your interest!
5. Introduction to R-Studio - In this introductory course, you will acquire the foundations to understand, execute and communicate data analysis in a widely-recognised software platform that was built for statistics. Over five days, you will gain valuable skills that you can market to employers, gain confidence in your ability to work with data, and create a knowledge base that you can build on for years to come.
6. Introduction to Text Analysis in Python - This course will teach you how to apply computational methods to text data in Python and extract insightful information from unstructured or semi-structured narratives. We will begin the journey into text mining by learning how to run a descriptive analysis and visualize text via word clouds. After that, we will investigate how to pre-process text data (tokenization, lemmatisation) and run more complex types of analysis, e.g. sensitivity analysis and text classification models. At the end of the course, you will be able to implement all that you have learned by working on a group project on the topic of your interest!
7. Introduction to NVivo
NVivo is a powerful and intuitive qualitative data analysis software for gaining richer insights from diverse data. This one day NVivo course will provide a practical, hands-on introduction to some of the features of the software, and cover the main operations and functions that a user will need to conduct analysis in NVivo. By the end of the session, you will be able to understand the structure of NVivo and how it can be used throughout a research project, navigate around the software and operate it to undertake analysis, understand the crucial role of analytic planning in employing NVivo tools powerfully, and more. This workshop is aimed at those who are refreshers for the latest version of NVivo. The focus is on achieving confidence in setting up a project efficiently, managing and organising data, exploring, and conceptualising data and interrogating and visualising data.
If you have any questions about the programme please email email@example.com