This free Spring Training Series will cover topics including, Foundations of Data Science, Introduction to Python, Basic Statistical Concepts, Data Exploration & Visualization, Experimentation in Data Science, and introduction to algorithmic techniques in Machine Learning.

This symposium explores how experts from different fields—ethics, data science, informatics, and epidemiology—work together to make sure health data are used responsibly. We will discuss real-world challenges like protecting people’s privacy, getting consent before using personal data, and ensuring that health decisions are fair for all communities, especially those who have been—and continue to be—underrepresented, underprivileged, or underserved (the "triple Us").

This panel discussion will center on reimagining the design and delivery of perinatal care to advance health equity and improve perinatal outcomes for all birthing people.