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| From | "info@physalia-courses.org" <info@physalia-courses.org> |
|---|---|
| Newsgroups | comp.lang.python |
| Subject | Machine Learning Methods for Longitudinal Data with Python – Online Course (6-9 May) |
| Date | 2025-02-28 12:56 +0100 |
| Message-ID | <mailman.121.1740748239.2912.python-list@python.org> (permalink) |
| References | <1740743787.06433745@webmail.jimdo.com> |
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 data Bias resolution: confounding, colliding, and mediator biases Time-series forecasting and predictive modeling Bayesian networks and graph models Applications in epidemiology, gene expression, and multi-omics The 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.D Physalia-courses DIRECTOR info@physalia-courses.org mobile: +49 17645230846 [ Bluesky ]( https://bsky.app/profile/physaliacourses.bsky.social ) [ Linkedin ]( https://www.linkedin.com/in/physalia-courses-a64418127/ )
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Machine Learning Methods for Longitudinal Data with Python – Online Course (6-9 May) "info@physalia-courses.org" <info@physalia-courses.org> - 2025-02-28 12:56 +0100
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