Visual Data Science

Objectives
The course studies the human side of data science. In particular, the course discusses how principles from visualization, visual analytics, perceptual psychology and cognitive sciences can be applied to data science in order to facilitate effective data exploration tools. Furthermore, the course introduces students to the principles of human computer interaction, interface design and effective data communication tailored for different audiences.

Content
The course is designed to teach students the full pipeline of human centered data analysis, from data acquisition, data preparation and management, data visualization, interaction and exploration and finally the effective communication of insights from the data. Furthermore, the course focuses on visualization, interaction models, principles of human computer interaction and aesthetics for visual design.

Upon completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge
The student

• has the ability to understand and evaluate visual presentations of information data
• has thorough understanding of the visualization and interaction techniques for data science tasks
• has gained deep knowledge about data models, graphical perception and effective methods for visual encoding and data interaction
• has acquired knowledge about effective human computer interaction and user interface design

Skills
The student

• is able to acquire, prepare and visualize data for effective findings communication
• is able to analyze data analysis tasks and is able to identify effective methods from the visualization field, statistics and machine learning suited for task requirements
• can evaluate the data quality and perform data cleaning
• can design effective user interfaces for data exploration and presentation solutions using modern programming techniques

General competence
The student

• gains the ability to critically assess the quality and truthfulness of data representation
• can effectively communicate data insights through visual representations
• can independently plan, structure and implement smaller scale software projects