Course Description

Viewing design problems as a collection of decision-making processes, data has been one of the important foundations for making such decisions. This course introduces the basics of data-related methods and cutting-edge applications using a programming language for computational practice. Through examples of data generated from human activities and nature, students will learn techniques in the representation, processing, analysis, learning, and visualization of data to gain insights, communicate information, and create for the intersection of data and design. The course will include field trips depending on availability and external collaborator, and the contents are subject to change to fulfill the course objectives.

Learning Outcome

At the end of this course, students will be able to:

  1. Conduct data analysis and gain insights within a given context.
  2. Employ advanced techniques to visualize and communicate information.
  3. Demonstrate ability to create for the intersection of data and design.

Course Instructors & Teaching Support

  • Lead Instructor: Dr. Wan Fang

Grading

Academic Integrity

  • This course follows the SUSTech Code of Academic Integrity. This course’s students must abide by the SUSTech Code of Academic Integrity. Any work submitted by a student in this course for academic credit will be the student’s work. Violations of the rules (e.g., cheating, copying, non-approved collaborations) will not be tolerated.

Course Materials

Lecture Notes

WeekMonday, 8:00-9:50Wednesday, 10:20-12:10Assignments DDL
01Lecture 01: Data Storytelling | Course Introduction
02Lecture 02: Introduction to Data | Dimensional Visualization of DataLecture 03: Design with Analytics | The Importance of Context
03Lecture 04: Concepts of Data X | Global Health DataTeam of 3 members
04Lecture 05: Data, Narrative, Visualization | Four Types of Data AnalyticsTutorial: 3-minute story & Big Idea
05Lecture 06: Data Quality Assessment | Practice with Python
06Lecture 07: Descriptive Statistics | Exploratory Data AnalysisTutorial
07Assignment 1 Presentation*Assignment 1:
Apr 2 @ 10:00
08Lecture 08: Inferential StatisticsLecture 9: Data-Driven Design | A/B Testing
09Interim ReviewSubmission:
Apr 16 @ 10:00
10Workshop I: D3 BasicLecture 10: Visual Encoding Design
11Lecture 11: DO and DON’T | Interaction
12Lecture 12: Uncertainty
13Workshop II: D3 Advance
14TutorialAssignment 2 Presentation*Assignment 2:
May 21 @ 10:00
15Lecture 14: Course Review
16Final Review PresentationFinal Project:
Jun 8 @ 23:30
17-18Final Exam参考课件:
Data Thinking,
EDA,
A/B Testing,
Visual Encoding Design
* Due to the number of enrolled students in this course, only half students are selected to present assignment 1 and the other half present assignment 2.

Instructions on Individual Assignments

Instructions on Team Project