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CREATED:20240918T091340Z
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UID:173184-1732525200-1732899600@www.scilifelab.se
SUMMARY:Biostatistics and Machine Learning II
DESCRIPTION:National course for PhD students\, researchers\, and other employees across Swedish universities who seek to deepen their biostatistical and machine learning skills.  Building on the Introduction to Biostatistics and Machine Learning course\, this course expands on common life science data analysis methods\, including dimensionality reduction techniques beyond PCA\, mixed-effects models for analysis of repeated measures\, and survival analysis. We will also dive deeper into machine learning\, covering more classification algorithms\, ensemble techniques\, optimization strategies and PLS methods for single and multi-omics data analysis. \n\n\n\n\n\n\n\nImportant dates\n\n\n\nApplication open: now \n\n\n\nApplication closes: 2024-10-18 \n\n\n\nConfirmation to accepted students:  2024-10-25 \n\n\n\nResponsible teachers:  Payam Emami\, Olga Dethlefsen\, Eva Freyhult \n\n\n\nIf you do not receive information according to the above dates please contact edu.ml-biostats@nbis.se \n\n\n\n\n\n\n\n\n\nApplication\n\n\n\n\n\nCourse website\n\n\n\n\n\n\n\n\n\nCourse fee\n\n\n\nA course fee of 3000 SEK for academic participants and 15 000 SEK for non-academic participants will be invoiced to accepted participants. The fee includes lunches\, coffee and snacks. \n\n\n\n*Please note that NBIS cannot invoice individuals \n\n\n\n\n\n\n\nCourse content\n\n\n\n\nDimensionality reduction techniques beyond PCA\n\n\n\nClassification algorithm and ensemble techniques\n\n\n\nMachine learning optimization strategies\n\n\n\nPLS-based methods for single and multi-omics data analysis\n\n\n\nMixed-effects models for repeated measures\, longitudinal studies and nested designs\n\n\n\nSurvival analysis\n\n\n\nIntroduction to neural networks\n\n\n\n\n\n\n\n\nEducation\n\n\n\nIn this course\, we focus on an active learning approach. The education consists of teaching blocks alternating between lectures\, group discussions\, live coding sessions etc. \n\n\n\n\n\n\n\nEntry requirements\n\n\n\n\nBasic R and Python data science skills (for more details see course website)\n\n\n\nHaving attended the Introduction to Biostatistics and Machine Learning course or having equivalent knowledge\n\n\n\nBYOL (bring your own laptop)\n\n\n\n\nThe course can accommodate a maximum of 24 participants. If we receive more applications\, participants will be selected based on several criteria. Selection criteria include correct entry requirements\, motivation to attend the course as well as gender and geographical balance.
URL:https://www.scilifelab.se/event/biostatistics-and-machine-learning-ii/
LOCATION:Navet\, SciLifeLab Uppsala\, SciLifeLab Uppsala\, BMC C11\, Husargatan 3\, Uppsala\, 75237\, Sweden
CATEGORIES:Course
ORGANIZER;CN="NBIS & Training Hub":MAILTO:traininghub@scilifelab.se
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