How to tell a story with data
What you'll learn
- Give better spoken and written presentations about data!
- Have an arsenal of strategies for creating memorable data stories.
- Know and apply the "5-stage arc" for memorable data storytelling.
Requirements
- An interest in improving data presentations.
Description
If you want to present data in a way that people will understand and remember, then you need to tell a story with the data. And if you want to learn how to tell a story with data, then this course is for you.
In this course, you’ll learn tips, tricks, and strategies for engaging your audience (both live audiences and reading audiences) to help them remember the key points of your data graphs. There are many examples and exercises, so you’ll learn how to do it in a way that’s both informative and engaging.
Why learn data storytelling
We live in a world increasingly dominated by data. Data are used to make important decisions, to shape business and political policy, and to understand the fundamental workings of nature. But data can be complicated, mysterious, and difficult to understand.
It is more important than ever to be able to communicate data in a way that is comprehensible and memorable. That's called data storytelling. Data storytelling is a skill, and the goal of this course is to help you improve this skill.
What you will get from this course
Very simple: An easy-to-apply framework for building audience excitement about your data.
Also: Lots of tips for making and presenting data graphics.
Who this course is for:
- Anyone from student to professional who wants to improve their data-storytelling skills.
Instructor
I am a neuroscientist (brain scientist) and associate professor at the Radboud University in the Netherlands. I have an active research lab that has been funded by the US, German, and Dutch governments, European Union, hospitals, and private organizations.
But you're here because of my teaching, so let me tell you about that:
I have 20 years of experience teaching programming, data analysis, signal processing, statistics, linear algebra, and experiment design. I've taught undergraduate students, PhD candidates, postdoctoral researchers, and full professors. I teach in "traditional" university courses, special week-long intensive courses, and Nobel prize-winning research labs. I have >80 hours of online lectures on neuroscience data analysis that you can find on my website and youtube channel. And I've written several technical books about these topics with a few more on the way.
I'm not trying to show off -- I'm trying to convince you that you've come to the right place to maximize your learning from an instructor who has spent two decades refining and perfecting his teaching style.
Over 120,000 students have watched over 7,500,000 minutes of my courses. Come find out why!
I have several free courses that you can enroll in. Try them out! You got nothing to lose ;)
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By popular request, here are suggested course progressions for various educational goals:
MATLAB programming: MATLAB onramp; Master MATLAB; Image Processing
Python programming: Master Python programming by solving scientific projects; Master Math by Coding in Python
Applied linear algebra: Complete Linear Algebra; Dimension Reduction
Signal processing: Understand the Fourier Transform; Generate and visualize data; Signal Processing; Neural signal processing