> For the complete documentation index, see [llms.txt](https://x.ancorasir.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://x.ancorasir.com/ds363/ds363-design-and-learning-with-data.md).

# \[DS363] Design and Learning with Data

2025 Spring

## 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 Outcomes

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 Instructor & Teaching Team

* **Lead Instructor**: Dr. Wan Fang
  * <wanf@sustech.edu.cn>
  * Tuesdays between 1000 and 1200
  * Level 3, Block C1, Wisdom Park
* **Teaching Assistant**: Cheng Sirui
  * <12433266@mail.sustech.edu.cn>

## Grading Policy

![DS363 2025 Spring grading: attendance 10%, assignments 20%, project 50%, exam 20%](https://content.gitbook.com/content/7NwmpipDq0oVPifIXgb0/blobs/4aoS3V3F3X6kK0GEnR8q/assets/Grading-structure.jpeg)

### Instructions on Individual Assignments

![Assignment 1: Practising Data Discovery — original task and notes](https://content.gitbook.com/content/7NwmpipDq0oVPifIXgb0/blobs/VEl68gdZriLt6TDbAFRz/assets/A1.png)

![Assignment 2: Interactive Visualization — original task and notes](https://content.gitbook.com/content/7NwmpipDq0oVPifIXgb0/blobs/N98s6rFdPjIxl2ULWmdm/assets/Screenshot-2025-03-24-at-11.08.11.png)

### Instructions on Team Project

![Team Project: Mid-Term Presentation — original task and notes](https://content.gitbook.com/content/7NwmpipDq0oVPifIXgb0/blobs/gw9qYs8fb5kNdVLwBSic/assets/Screenshot-2025-03-24-at-11.13.10.png)

![Course Project: Final Showcase — original task and notes](https://content.gitbook.com/content/7NwmpipDq0oVPifIXgb0/blobs/QOVFM0eMKVwBuV41VcAE/assets/Screenshot-2025-03-24-at-11.18.03.png)

## 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.

## Recommended Textbook(s)

* (2008) [Handbook of Data Visualization](https://link.springer.com/book/10.1007/978-3-540-33037-0), Chun-houh Chen, Springer
* (2015) [Storytelling with Data](https://github.com/Saurav6789/Books-/raw/master/storytelling-with-data-cole-nussbaumer-knaflic.pdf), Cole Nussbaumer Knaflic, Wiley
* (2001) [The Visual Display of Quantitative Information](http://faculty.salisbury.edu/~jtanderson/teaching/cosc311/fa21/files/tufte.pdf), Edward R. Tufte, Graphics Press

## Teaching Schedule

**Lecture 01:** [**Data Storytelling | Course Introduction**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/25Spring-DS363-Lecture-1.pdf) | Wed, 1020–1210

**Lecture 02:** [**Introduction to Data | Dimensional Visualization of Data**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/25Spring-DS363-Lecture-2.pdf) | Mon, 0800–0950

**Lecture 03:** [**Design with Analytics |**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/25Spring-DS363-Lecture-3.pdf) [**The Importance of Context**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/25Spring-DS363-Lecture-3.pdf) | Wed, 1020–1210

**Lecture 04:** [**Concepts of Data X**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/25Spring-DS363-Lecture-4.pdf) **|** [**Global Health Data**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/25Spring-DS363-Lecture-4_Global-Health.pdf) | Wed, 1020–1210

* Team of 3 members

**Lecture 05:** [**Data, Narrative, Visualization | Four Types of Data Analytics**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/25Spring-DS363-Lecture-5.pdf) | Mon, 0800–0950

**Tutorial: 3-minute story & Big Idea** | Wed, 1020–1210

**Lecture 06:** [**Data Quality Assessment**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/25Spring-DS363-Lecture-6.pdf) **|** [**Practice with Python**](https://bionicdl.feishu.cn/docx/IfFrd8sFAotPwcxROxjcJ18Mndc) | Wed, 1020–1210

**Lecture 07:** [**Descriptive Statistics | Exploratory Data Analysis**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/25Spring-DS363-Lecture-7.pdf) | Mon, 0800–0950

**Tutorial** | Wed, 1020–1210

**Assignment 1 Presentation\*** | Wed, 1020–1210

* Assignment 1: Apr 2 @ 10:00

**Lecture 08:** [**Inferential Statistics**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/25Spring-DS363-Lecture-8.pdf) | Mon, 0800–0950

**Lecture 9:** [**Data-Driven Design**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/25Spring-DS363-Lecture-9.pdf) **|** [**A/B Testing**](https://bionicdl.feishu.cn/docx/SNIAdLH6HoVDohx1fNbc6cY0n5c) | Wed, 1020–1210

**Interim Review** | Wed, 1020–1210

* Submission: Apr 16 @ 10:00

**Workshop I:** [**D3 Basic**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/1-intro.pptx) | Mon, 0800–0950

**Lecture 10:** [**Visual Encoding Design**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/25Spring-DS363-Lecture-10-Visual-Encoding-Design.pdf) | Wed, 1020–1210

**Lecture 11:** [**DO and DON’T | Interaction**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/25Spring-DS363-Lecture-11.pdf) | Wed, 1020–1210

**Workshop II:** [**D3 Advanced**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/2.pptx) | Wed, 1020–1210

**Lecture 12:** [**Uncertainty**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/25Spring-DS363-Lecture-12.pdf) | Wed, 1020–1210

**Tutorial** | Mon, 0800–0950

**Assignment 2 Presentation\*** | Wed, 1020–1210

* Assignment 2: May 21 @ 10:00

**Lecture 14:** [**Course Review**](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/24Spring-DS363-Course-Review.pdf) | Wed, 1020–1210

**Final Review Presentation** | Wed, 1020–1210

* Final Project: Jun 8 @ 23:30

**Final Exam**

* 参考课件： [Data Thinking](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/Exam_reference_Module-02-Data-Thinking.pdf), [EDA](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/Exam_reference_Module-03-Data-Discovery-EDA.pdf), [A/B Testing](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/Exam_reference_Module-03-AB-Testing.pdf), [Visual Encoding Design](https://github.com/asMagicBrain/DS363/blob/main/2025-spring/Exam_reference_Module-04-Visual-Encoding-Design.pdf)

**\*** 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**.

## Important Deadlines

* Apr 2 @ 10:00: Assignment 1.
* Apr 16 @ 10:00: Submission — Interim Review.
* May 21 @ 10:00: Assignment 2.
* Jun 8 @ 23:30: Final Project.


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