Data Storytelling
Purdue's Data Storytelling Certificate teaches online courses that combine data science, storytelling, and visualization. The program includes four courses and offers a free prerequisite course, Data Storytelling 101. Professionals can choose individual courses or complete the full certificate, enhancing their data communication and interpretation skills.
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Overview
Unlock the power of data with Purdue’s Data Storytelling Certificate program.
Unlock the power of data with Purdue’s Data Storytelling Certificate program. Learn to transform raw numbers into compelling narratives. Ideal for professionals in various fields, this online series of four courses blends rhetoric, data science, and storytelling to create impactful data stories.
Enroll individually or as a bundle, with Data Storytelling 101 as the essential first step. Taught by Dr. Sorin Adam Matei, an expert in communication and technology, this program equips you to excel in data communication and storytelling, regardless of your prior statistical knowledge.
Program Specifics
Learn more about the Data Storytelling Certificate
The Data Storytelling Certificate program is a series of four courses available 100% online. The courses combine elements of rhetoric, data science, visualization and storytelling to form a cohesive and unique plan of study. Each of the 4 courses are subdivided into 6 modules. The first course, Data Storytelling 101, is free for students who also register for a paid course.
Data Storytelling 101 offers an introduction to the concept of Data Storytelling, why it matters, and how it can transform the results of your research into impactful narratives through which your audience learns new things, remembers important findings and then acts on them. This course must be taken before you start any of the other paid courses.
Data Storytelling 101 is an introduction course that is required prior to taking the remaining three courses. Students do not individually register for the Data Storytelling course but must register for one or all of the remaining three courses. Once registered for any other course, the student will also receive notification for access to Data Storytelling 101.
Learning outcomes: Provide examples and justify all core techniques in storytelling, including challenging prior assumptions, providing alternative explanations, balancing timing versus immediacy, and transforming each story into a teachable moment.
This course teaches students how to think about research – from data collection to data analysis to reporting results – as a narrative process. Rooted in basic statistics, the course provides students who have some numeric literacy a clear and direct path for advancing from reportable results to stories with impact. Students will especially learn how to construct numeric stories that demonstrate causality.
Learning outcomes: Enumerate and defend the core relationships between research design and story-building, as well as define a valid causal inference and possible fallacies. Generate hypotheses based on data, explain how the hypotheses could be tested, and show how to translate different experimental designs and data pools into stories
This course provides key strategies for visualizing results and enhancing the visual communication of data stories, followed by a deeper dive into how to go from analysis of results to a compelling story enhanced with visuals.
Learning outcomes: Create specific data visualizations that carry forward casual narratives, such as stacked bar charts, time series, and multidimensional causal chains, using effective and recognized visual and charting building blocks. Become familiar with how to avoid common pitfalls in designing visual content with narrative goals. Identify story elements that map onto the five narrative techniques learned and demonstrate through written compositions the ability to use them effectively.
In this course, students learn how to create data stories that use ethical research and protect basic human rights: autonomy, fairness, trust, beneficence, and non-malevolence.
Learning outcomes: Define and use appropriate checks and reasoning processes for ensuring data transparency, validity, and ethical use. Identify the effect of a story by the amount of belief change it induces in an audience, determine the threshold of significance for various audiences, and use the amount and type of learning for each story to predict the degree to which it could be an actionable story or not.
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