Brief Course Description
1. Course Title:
Data Visualization
2. Language of Instruction:
Tiếng Anh
3. Course Code:
TEC550066
4. Credits:
3
5. Course Objectives:
The objective of this course is to equip students with the knowledge and skills necessary for data visualization, helping users to easily analyze and make decisions. Specifically, students will master the basic concepts and tools for data visualization, thereby creating effective reports and visual charts. Students will learn how to use visualization software and tools to convert data into graphical representations. The course encourages students to carry out projects that apply data and technology, thereby improving their practical skills and ability to work in groups. Students will develop skills in data analysis, evaluation and selection of appropriate tools and software for data visualization, meeting the needs of business projects and technology innovation. Students will be equipped with a solid foundation for continuing to learn, develop the ability to work independently or on projects, and translate data science into useful information in a business environment.
6. Brief Description of Course Content:
This module focuses on building creative and business skills to transform data into visual reports for the purpose of generating understanding, perception, inference, and information simplification. Students will learn how to use software to enter, organize, and visualize data emphasizing the application of principles of graphic design, perceptual art, and perceptual psychology to the creation of graphs and pages. a clear, elegant overview that conveys the essence of the insights, messages, or recommendations distilled from the data. Students will become familiar with exploratory and explanatory data visualization techniques for presentation and storytelling. In addition, students will work together on group projects to develop data visualization skills from a business project or technology creation, thereby perfecting competencies; visual thinking, data analysis, choice of visualization technology, reader-oriented design, and data normalization/ethicalization.