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title: AI and Probabilistic Programming for Global Health in Africa | ||
subtitle: A hands-on course for students and researchers at the intersection of probabilistic programming, statistics, AI and global health. | ||
summary: Imperial College London and the Machine Learning and Global Health Network will host a course from March 24–28, 2025, at AIMS in Cape Town. This one-week, hands-on course is designed for students and researchers working at the intersection of statistics and public health. Participants will learn how to integrate modern statistical techniques with the Stan probabilistic programming language to address a wide range of applications, including epidemiological, genomic, and spatial data. | ||
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lastmod: 2024-11-18 | ||
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# Listing view | ||
view: card | ||
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banner: | ||
caption: '' | ||
image: '' | ||
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p { | ||
text-align: justify; | ||
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a.button { | ||
padding: 8px 8px; | ||
border: 1x outset buttonborder; | ||
border-radius: 15px; | ||
color: white; | ||
background-color: rgb(0, 191, 255); | ||
text-decoration: none; | ||
font-size:25px | ||
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**When:** 24th - 28th March 2025 | ||
<br> | ||
**Where:** AIMS, Cape Town, South Africa | ||
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Imperial College London and AIMS South Africa are pleased to offer a new 1 week short course in Modern Statistics and Global Health. This course is targeted at Masters level students and above with a background in statistics and/or data science, who are interested in modern statistical methods with applications in global population health. | ||
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Attendees will learn how to: | ||
+ Write their own models in the probabilistic programming language Stan, carry out full Bayesian inference and assess model convergence, | ||
+ Implement advanced statistical models including mixed effects models for hierarchical data, non-parametric gaussian process regression models and computationally scalable approximations, | ||
+ Implement compartmental models for infectious disease epidemiology, | ||
+ Implement a full phylogenetic analysis pipeline for the analysis of pathogen genomic data, | ||
+ Interpret results and present findings | ||
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Attendees will learn on the course through a blended mix of lectures, hands-on computer practicals and guided tutorials, group work and presenting to their peers. | ||
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**Pre-requisites:** Good knowledge of Python and git | ||
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**Deadline to apply:** 31 January 2025 | ||
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<center> | ||
<a href="https://mlgh.net/sa_aimsximperial2025/overview/" class="button">More information<a/> | ||
<a href="https://mlgh.net/sa_aimsximperial2025/application/" class="button">Apply<a/> | ||
</center> | ||
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