Course overview

The primary goal of this course is to introduce the key principles, methods, and techniques for effective visual data analysis. Students will explore various visualization systems and tools through practical exercises, learning how to present different data types and critically analyze existing designs.

1. Course Learning Outcomes

CLO 1. Understand the principles of data and graphic design.

CLO 2. Create well-designed data visualizations with appropriate tools.

CLO 3. Evaluate a visualization design.

2. Workload and Requirements

• Credits: 4 credits (3 Lecture credits + 1 lab credit).
• Self-Study: Students are expected to spend at least 8 hours per week on reading, exercises, and assignments.
• Attendance: A minimum of 80% attendance is compulsory.
• Passing Grade: Students must earn more than 50/100 points overall.
• Prerequisites: none

3. Textbook and reading material

1. Tamara Munzner, Visualization Analysis and Design 1st edition, 2014
2. Cole Nussbaumer Knaflic, Storytelling with Data: A Data Visualization Guide for Business Professionals 1st edition, 2015
3. Edward R. Tufte, The Visual Display of Quantitative Information, 2nd edition, 2001 

4. Lecturers

1. Dr. Trần Thanh Tùng
2. Dr. Lê Hải Dương
3. Dr. Vi Chí Thành 

Contact:  Dr. Trần Thanh Tùng - tttung@hcmiu.edu.vn

5. Grading

The course is graded on the following scale: