> 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/ds363/2024-spring/ds363-design-and-learning-with-data.md).

# \[DS363] Design and Learning with Data

2024 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**: Zhang Zihan
  * `12333210@mail.sustech.edu.cn`

## Grading Policy

![DS363 2024 Spring grading: attendance 10%, assignments 20%, project 50%, exam 20%](https://content.gitbook.com/content/mQFLh6re8rNCkXFOa89s/blobs/cEB7gPcMBHlZYoKjEde0/assets/Grading-structure.jpeg)

### Instructions on Individual Assignments

![Assignment 1: practising Data Discovery — original task and notes](https://content.gitbook.com/content/mQFLh6re8rNCkXFOa89s/blobs/GuYbaDszowTYvDE0FwDm/assets/Assignment1-1.jpeg)

![Assignment 2: Interactive Visualization — original task and notes](https://content.gitbook.com/content/mQFLh6re8rNCkXFOa89s/blobs/qew7V13u1m2jaOsAxbFy/assets/assignment2-2.jpeg)

### Instructions on Team Project

* Form a team of **2 members** for the final project
* The details of the final showcase presentation are subject to change according to the number of total projects

![Team Project: Milestone Presentation — original task and notes](https://content.gitbook.com/content/mQFLh6re8rNCkXFOa89s/blobs/FRuufQFutuIrBmNWuvUl/assets/milestone.jpeg)

![Course Project: Final Showcase — original task and notes](https://content.gitbook.com/content/mQFLh6re8rNCkXFOa89s/blobs/F1OzEx2aTKqFzerMcnN7/assets/final.jpeg)

## 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/2024-spring/24Spring-DS363-Module-01-Lecture-1.pdf) | Tue, 1400–1550

**Lecture 02:** [**Introduction to Data | Basic Visualization of Data**](https://github.com/asMagicBrain/DS363/blob/main/2024-spring/24Spring-DS363-Module-01-Lecture-2.pdf) | Tue, 1400–1550

**Lecture 03:** [**The Importance of Context | Design with Analytics**](https://github.com/asMagicBrain/DS363/blob/main/2024-spring/24Spring-DS363-Module-01-Lecture-3.pdf) | Fri, 1400–1550

**Lecture 04:** [**Concepts of Data X | Data X by Examples**](https://github.com/asMagicBrain/DS363/blob/main/2024-spring/24Spring-DS363-Module-02-Lecture-1.pdf) | Tue, 1400–1550

* Team of 2 members (or 1 if you could find a teammate)

**Lecture 05:** [**Data, Narrative, Visualization | Four Types of Data Analytics**](https://github.com/asMagicBrain/DS363/blob/main/2024-spring/24Spring-DS363-Module-02-Lecture-2.pdf) | Tue, 1400–1550

**Team Project Presentation: 3-minute story & Big Idea** | Fri, 1400–1550

* Slides Submission: Mar 14 @ 23:30

**Lecture 06:** [**Data Quality Assessment**](https://github.com/asMagicBrain/DS363/blob/main/2024-spring/24Spring-DS363-Module-03-Lecture-1.pdf) **|** [**Practice with Python**](https://bionicdl.feishu.cn/docx/IfFrd8sFAotPwcxROxjcJ18Mndc) | Tue, 1400–1550

**Lecture 07:** [**Descriptive Statistics | Exploratory Data Analysis**](https://github.com/asMagicBrain/DS363/blob/main/2024-spring/24Spring-DS363-Module-03-Lecture-2.pdf) | Tue, 1400–1550

**Lecture 08:** [**Inferential Statistics**](https://github.com/asMagicBrain/DS363/blob/main/2024-spring/24Spring-DS363-Module-03-Lecture-3.pdf) | Fri, 1400–1550

**Assignment 1 Presentation\*** | Tue, 1400–1550

* Assignment 1: Apr 1 @ 23:30

**Lecture 13:** [**Data-Driven Design | A/B Testing**](https://github.com/asMagicBrain/DS363/blob/main/2024-spring/24Spring-DS363-Module-03-Lecture-4.pdf) | Tue, 1400–1550

**Guest Lecture** | Fri, 1400–1550

**Interim Review** | Tue, 1400–1550

* Slides Submission: Apr 15 @ 23:30

**Lecture 09:** [**Visual Encoding Design**](https://bionicdl.feishu.cn/docx/Df2TdeotDoeRMNxPqjhccSd1nGF) | Tue, 1400–1550

**Lecture 10: Tableau Basics by TA** | Fri, 1400–1550

**Lecture 11:** [**DO and DON’T | Interaction**](https://github.com/asMagicBrain/DS363/blob/main/2024-spring/24Spring-DS363-Module-04-Lecture-2.pdf) | Tue, 1400–1550

**Lecture 12: Advanced Charts in Tableau by TA** | Tue, 1400–1550

**Tutorial** | Fri, 1400–1550

**Assignment 2 Presentation\*** | Tue, 1400–1550

* Assignment 2: May 13 @ 23:30

**Lecture 13:** [**Uncertainty**](https://github.com/asMagicBrain/DS363/blob/main/2024-spring/24Spring-DS363-Module-05-Lecture-1.pdf) | Tue, 1400–1550

**Tutorial** | Fri, 1400–1550

**Tutorial** | Tue, 1400–1550

**Lecture 14:** [**Course Review**](https://github.com/asMagicBrain/DS363/blob/main/2024-spring/24Spring-DS363-Course-Review.pdf) | Tue, 1400–1550

**Final Review** | Fri, 1400–1550

* Final Project: Jun 9 @ 23:30

**Final Exam** | Tue Jun 18, 1400–1600 | 三教303

* 参考课件：[Data Thinking](https://github.com/asMagicBrain/DS363/blob/main/2024-spring/Exam_reference_Module-02-Data-Thinking.pdf), [EDA](https://github.com/asMagicBrain/DS363/blob/main/2024-spring/Exam_reference_Module-03-Data-Discovery-EDA.pdf), [A/B Testing](https://github.com/asMagicBrain/DS363/blob/main/2024-spring/Exam_reference_Module-03-AB-Testing.pdf), [Visual Encoding Design](https://github.com/asMagicBrain/DS363/blob/main/2024-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

* Mar 14 @ 23:30: Slides Submission — Team Project Presentation: 3-minute story & Big Idea.
* Apr 1 @ 23:30: Assignment 1.
* Apr 15 @ 23:30: Slides Submission — Interim Review.
* May 13 @ 23:30: Assignment 2.
* Jun 9 @ 23:30: Final Project.


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