Applied Visual Analytics

In a data-driven world, it is important to be able to analyze large amounts of data to identify patterns of interest and test hypotheses about them. Visual Analytics provides us with an interactive process of analytical reasoning facilitated by data visualization, combining the strengths of humans and computers in order to derive insight from massive, dynamic, ambiguous, and often conflicting data.

In this course we will introduce basic concepts of data visualization, how to apply them to build interactive interfaces for data sets of different types, and which tools are useful in this process.

Target group

This course is for experienced developers working in the industry with an interest in data analysis and visualization.

Content

Foundations of perception and design that are important for creating new visualizations.
Comparison between different types of visualization that work better for different types of data.
Integration of multiple individual visualizations into interactive dashboards.
Overview of the exploratory visual analysis process that incorporates all the above into a unified pipeline.
Practical applications using interactive visualization libraries.

The goal for the course is that the participants should be able to:

Critically and independently search, analyze and summarize relevant research results in visualization.
Efficiently integrate different visualizations into interactive dashboards, with the goal of exploring complex datasets from different perspectives simultaneously.
Design and develop visual analytics systems for the analysis of large and complex datasets, including the entire chain from raw data to insights.

For more detailed information about the course see the syllabus: https://kursplan.lnu.se/kursplaner/kursplan-4DV118-1.pdf

Practical information

All materials will be available digitally, including reading materials, lecture slides, videos, practical exercises, etc. The course will be given in a flexible manner to facilitate the combination of course work with your professional commitments. We recommend that you work on a project during the course that you can use in your daily work, with your own data, and your own problems.

The course is based on online activities to make it easier for you to combine your daily work with these studies. There will be pre-recorded lectures of foundational concepts, with focus on theories, ideas, and elements of the literature on Data Visualization and Visual Analytics. These will be complemented with pre-recorded tutorials of practical elements related to the course, such as the use of programming libraries and available tools.

In order to integrate with the teacher and other participants we offer weekly online tutoring sessions open to all participants for general questions, support with practical issues, or any other student needs. There will also be two mandatory on-site workshops focusing on interaction between teacher and participants to share real-world experiences and insights.

The course is assessed through 3 mandatory assignments, mandatory seminars, and active participation in discussion forums and workshops.

The total effort to complete this course is generally around 80 hours (or 8h a week).

Language of instruction: English.

Entry requirements

The basic eligibility for this course is a Bachelor degree. Candidates with relevant work experience are also invited to apply. Two years of relevant work experience is considered equivalent to one year of university studies at the Bachelor level.

Schedule

No date set.

This course is developed within the project Smart Industry phase 2 and funded by the Swedish Knowledge Foundation (KK-stiftelsen).

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