Visual Analytics Bootcamp

Overview

Academic Lead: Dr Sebastian Del Bano Rollin

Syllabus: SUM503M Visual Analytics Bootcamp [PDF]

This course is centered on hands-on projects to provide students with practical experience.  
The range of data examples are general and cover a broad range of subject areas and industries.

The course covers the following broad areas:

1) Acquisition and preparation of data.  EDA. Basic Visualizations. Best practices.

2) Visual Analytics of geospatial data (geographical data, MRI scan data,...)

3) Time series data. Visualization of trends, seasonalities and cycles. Possible applications to medical data (eg. apnea incidence, brain signals) or social media sentiment analysis. Building interactive dashboards and reporting results.

Course content is subject to change.

Course aims

The module aims to equip students with practical skills in data analysis and visualization techniques essential for extracting actionable insights from complex datasets. The real-world oriented lab sessions and project will help students learn about in exploratory data analysis, geospatial visualization, and interactive dashboard development. Students will gain skills that are highly valued across a wide set of academic and business fields.

Teaching and learning

You will be taught through a combination of lectures, laboratory work, and workshops.

Learning outcomes

You will learn/develop:

• the foundations of visual analytics, including the importance of visual perception, data visualization techniques, and best practices for communication using visualizations.
• apply a range of visual analysis techniques to the exploration and analysis of complex data. 
• effectively communicate results of data analysis by using visualizations appropriate for each project. Including dashboards, interactive charts, to improve user experience.

You will develop/be able to:

• develop the ability to research technologies needed for a new project and test different approaches for the data processing pipeline from data acquisition to presentation of results.
• collaborate with other students with diverse backgrounds and learn of the importance of creating working synnergies in a team. This is critical given the very broad and multidisciplinary nature of many data projects.
• understand the global nature of a data project from inception, data acquisition, analysis and reporting with particular emphasis on the visual exploration and communication aspects

Fees

Additional costs

All reading material will be provided online, so it is not necessary to purchase any books.

For course and housing fees visit our finance webpage

Entry requirements

Course prerequisites:

Basic statistics, elementary usage of a computer, basic computer literacy either Windows or Apple, or Linux.

We welcome Summer School students from around the world. We accept a range of qualifications

How to apply

Have a question? Get in touch - one of the team will be happy to help!

Applications close 26 May 2025