Dear all,There are still 5 seats left for the upcoming Physalia course "Machine Learning Methods for Longitudinal Data with Python," which is taking place online from 6-9 May. This course will provide a comprehensive introduction to analyzing sequence
data (repeated over time or space) when time and causation play a crucial role. This course will cover both classical statistical and modern machine learning approaches to handling time-dependent data. Participants will learn how to recognize and
address temporal dependencies, disentangle cause-effect relationships, and apply appropriate modeling techniques for forecasting, survival analysis, and multi-omics data integration. Topics will include:Statistical and machine learning methods for
sequence dataBias resolution: confounding, colliding, and mediator biasesTime-series forecasting and predictive modelingBayesian networks and graph modelsApplications in epidemiology, gene expression, and multi-omicsThe course combines lectures,
hands-on exercises, and case studies to ensure participants gain practical skills for applying these methods to real-world biological data. To register or learn more, please visit [ https://www.physalia-courses.org/courses-workshops/longitudinal-data/
]( https://www.physalia-courses.org/courses-workshops/longitudinal-data/ ) Best regards,Carlo --------------------Carlo Pecoraro, Ph.DPhysalia-courses DIRECTORinfo@physalia-courses.orgmobile: +49 17645230846[ Bluesky ]( https://bsky.
app/profile/physaliacourses.bsky.social ) [ Linkedin ]( https://www.linkedin.com/in/physalia-courses-a64418127/ )

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