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Data Visualization

Objectives

This course will combine the skills learned from Data Curation with essential data visualization techniques to showcase how to communicate effectively with data in a business setting. Students discover the power of storytelling with data through real-world business applications and gain hands-on training experience using Tableau Software. 

 

General characterization

Code

2491

Credits

3.5

Responsible teacher

Ji Rongjiao

Hours

Weekly - Available soon

Total - Available soon

Teaching language

English

Prerequisites

n/a 


Bibliography

This course does not require any textbook, because data science is a rapidly changing field and no textbook may cover all materials we will
teach in the course. However, the following book is recommended for your reference:
Storytelling with Data: A Data Visualization Guide for Business Professionals
The Wall Street Journal Guide to Information Graphics: The Dos and Don'ts of Presenting Data, Facts, and Figures

Teaching method

Students are required to bring own laptops for in-class exercises and quizzes.

This course adopts learning-by-doing culture that allows students to implement data visualization process through programming in Tableau, but basic Python (pandas in particular) and data curation concepts are expected. E.g., we expect that students are familiar with pivot tables. Most of class material will be in Tableau and presentations in pdf. 


Evaluation method

The overall evaluation of performance consists of 3 parts:

Class participation through 4 quizzes (20%)
Group project (30%)
Final exam (50%)

Subject matter

Data visualization plays an essential role in the understanding of both small and large-scale data. This course covers the fundamentals of
statistical exploration and visualization of data. We will show how to go beyond conventional tools to reach the root of data, and how to use data
to create an engaging, informative, compelling story. Students learn how to produce specialized visualizations to explore data in a detailed and
statistics-oriented manner.