Data and visual analytics is an emerging field concerned with analyzing, modeling, and visualizing complex high dimensional data.
This course will introduce students to the field by covering state-of-the-art modeling, analysis and visualization techniques. It will emphasize practical challenges involving complex real world data and include case studies and hands-on work with a high-level programming language using either Python or the R programming language for the purpose of communicating relevant data patterns in the form of graphical displays.
The course covers classical descriptive statistics and data visualization. Classical descriptive statistics includes how to draw conclusions about the distribution of data using graphs andcovers how to summarize data using measures of center, spread and association, and how to analyze data using normal distribution.
The course covers fundamentals of data-driven information visualization. It introduces how graphical elements and colour theory, design aspects, and perception affect how figures are perceived. The term visual literacy is introduced together with Tufte’s principles of scientific graphics. Visualisation of different data types, including categorical and textual data, is also covered in the course.
Literature lists are published at the latest one month ahead of the course start date.
To Literature ListAsk us about studying at Dalarna University.
support@du.se
+46 23-77 88 88
In the learning platform Learn you can find more information about the course.
Visit the course roomData and visual analytics is an emerging field concerned with analyzing, modeling, and visualizing complex high dimensional data.
This course will introduce students to the field by covering state-of-the-art modeling, analysis and visualization techniques. It will emphasize practical challenges involving complex real world data and include case studies and hands-on work with a high-level programming language using either Python or the R programming language for the purpose of communicating relevant data patterns in the form of graphical displays.
The course covers classical descriptive statistics and data visualization. Classical descriptive statistics includes how to draw conclusions about the distribution of data using graphs andcovers how to summarize data using measures of center, spread and association, and how to analyze data using normal distribution.
The course covers fundamentals of data-driven information visualization. It introduces how graphical elements and colour theory, design aspects, and perception affect how figures are perceived. The term visual literacy is introduced together with Tufte’s principles of scientific graphics. Visualisation of different data types, including categorical and textual data, is also covered in the course.
Literature lists are published at the latest one month ahead of the course start date.
To Literature ListAsk us about studying at Dalarna University.
support@du.se
+46 23-77 88 88
In the learning platform Learn you can find more information about the course.
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