Rising diabetes cases worldwide pose a significant healthcare challenge. Early detection is key to mitigating severe health outcomes, but extracting meaningful insights from the volume and complexity of healthcare data can be daunting. In this course, Data Visualization for Storytelling, you’ll gain the ability to transform complex health data into compelling visual narratives that can inform policy decisions and support early diabetes detection strategies. First, you’ll explore the foundational principles of data visualization, learning how to choose the right visualization based on the characteristics of the data. Next, you’ll discover how to design effective, visually appealing data visualizations that highlight key insights and patterns in the data. Finally, you’ll learn how to incorporate interactivity into your data visualizations, use advanced visualization techniques, and apply these skills to a real-world case study: the Diabetes Prediction Dataset. When you’re finished with this course, you’ll have the skills and knowledge of data visualization needed to transform complex datasets into clear, insightful visual narratives, and be well-equipped to use these skills in various fields.
Author Name: Pratheerth Padman
Author Description:
Pratheerth is a Data Scientist who has entered the field after an eclectic mix of educational and work experiences. He has a Bachelor’s in Engineering in Mechatronics from India, Masters in Engineering Management from Australia and then a couple of years of work experience as a Production Engineer in the Middle East. Then when the A.I bug bit him, he dropped everything to dedicate his life to the field. He is currently working on mentoring, course creation and freelancing as a Data Scientist.