| Pre-Requisites | DA190 |
| Co-Requisites | None |
| Instructional Hours | 40 |
| Instructional Mode | Lecture |
| Delivery Mode | In-Person / Blended / Online |
This course, Data Visualization and Storytelling (DS290), covers techniques for creating effective data visualizations and communicating data-driven insights through compelling narratives. Data visualization is the graphical representation of information and data, and it plays a crucial role in data analysis and communication. In this course, students will learn how to create meaningful and impactful data visualizations to present complex information in a clear and engaging manner.
By the end of this course, students will be able to:
The course content will be presented through a series of lectures, hands-on workshops, and projects. Students will be evaluated through assignments, a final project, and class participation.
Throughout the semester, students will be given assignments that will require them to create various data visualizations and narratives based on real-world data sets. These assignments will allow students to practice their data visualization and storytelling skills.
The final project for this course will involve creating a comprehensive data visualization and storytelling project. Students will have the opportunity to apply all the skills learned throughout the course to present a compelling narrative based on a real-world data set. The final project will count towards a significant portion of the overall course grade.
The following is a general outline of the topics covered in the course:
| Week | Topic |
|---|---|
| 1 | Introduction to Data Visualization and Storytelling |
| 2 | Principles of Effective Data Visualization |
| 3 | Tools for Data Visualization |
| 4 | Data Visualization Techniques |
| 5 | Interactive Data Visualization |
| 6 | Design Principles for Data Visualization |
| 7 | Storytelling with Data |
| 8 | Case Studies in Data Visualization and Storytelling |
| 9 | Ethics and Bias in Data Visualization |
| 10 | Visualizing Big Data |
| 11 | Data Visualization for Decision Making |
| 12 | Final Project Presentations and Course Reflection |