• Gain an insight into the different data analytics needs in the sector of your interest.
• Explore your interest for further data analytics training under a Q-Step Proficiency in Applied Data Analysis degree.
• Increase knowledge of sector specific activities
• Learn in an interactive and experiential environment
• Work with students from different year groups, subjects and levels of degree
• Be inspired by experienced professionals
• Gain confidence in your abilities
• Develop your career plan
• Apply newly acquired learning to a group project as part of the training
• Receive a certificate and reference

You must be a current University of Exeter student when you apply for the programme. We welcome applications from all disciplines and levels of study, as long as you can demonstrate a keen interest in this subject area.

We particularly welcome applications from groups currently underrepresented in the workforce.

You must have the right to work in the UK for the duration of the professional pathways .

The SMART Skills project has now ended. We are hoping to secure new funding to resume offering these or similar data analytic courses in 2024. 

Please continue to check back periodically - or follow the q-step twitter @ExeterQStep or instagram @exeteruniqstep for updates.

If you would like to be added to a mailing list to be notified when courses will be offered again, please complete this Microsft Form 

As part of the SMART Skills project, 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.

Example of the courses we delivered for this project are:

Critically Interpreting Data

Do you want to understand how to use data? 

We live in an increasingly data-driven world. Smart phones, smart watches and even smart fridges create and share data every second of the day. At the same time, data is misrepresented for political gain and an understanding of data has become crucial for comprehending the world around us. Too few people have the smart skills to interpret data and therefore use it responsibly.

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.

Misinformation in the Modern World

In this workshop, we are going to talk about different types of information disorder in the modern world (mis-, dis- and mal-information), from a social science perspective, and how they vary upon the criteria of falseness and intention to harm. We will then particularly focus on dis-information, its historical evoluation, the forms it takes, the factors that affect its dissemination, and the mechanisms by which it perpectuates. Finally, we will look into how social science studies conspiracy beliefs, what is the conspiratorial mentality, and how widespread conspiracist views are in the general population. 

Introduction to Python

In this course, we'll dive into learning Python from scratch and applying the skills of data analysis to a real-world dataset! Python is a flexible, intuitive programming language, perfect for those who are about to begin their pathway as a data analytic. Over the course of studying, we will touch upon the most crucial skills of working with data, such as exploring and subsetting the dataset, creating new variables, cleaning the data (e.g. missing values), visualizing the distribution of variables, as well as running statistical tests and inferring the relationship between two or more variables. At the end of the course you will have time to work on a group project on the topic of your interest! 

Introduction to RStudio

Why take this course?

STATISTICS is a scary word to many people. A statistic is simply a number, and here's the thing: you don't have to be a statistician to be confident working with data. Yet almost every role in every company requires an understanding of data, and many desired roles require data analysis experience. 

This course provides the foundations for you 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. 

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!

 Essentials in Excel

STATISTICS is a scary word to many people. A statistic is simply a number, and here's the thing: you don't have to be a statistician to be confident working with data. Yet almost every role in every company requires an understanding of data, and many desired roles require data analysis experience. 

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. 

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.

Unfortuately we will not be offering internship opportunities under the new programme. 

If you would like to ask any questions, please contact the Q-Step Centre team: qstep@exeter.ac.uk