Merge pull request #41 from tristan-myles/main

Updates title, header, programme, & application

content/sa_aimsximperial2025/application/_index.md

@@ -11,10 +11,9 @@
 </style>
 
 <center>
-<img src="../resources/imperial.png" width="250" hspace="50" style="display:inline-block;margin:10px;"/>
+<img src="../resources/imperial.png" width="250" style="display:inline-block;margin:5px;"/>
 <img src="../resources/mlgh.png" width="200" hspace="50" style="display:inline-block;margin:50px;"/>
-<img src="../resources/ammi.png" width="200" style="display:inline-block;"/>
-</center>
+<img src="../resources/ammi.png" width="200" style="display:inline-block;margin:-3px"/></center>
 
 # Application
 **Cost: R3,600 (ZAR)**
@@ -23,14 +22,15 @@
 <br/>
 **Deadline to apply:** 31th January 2025
 
-Form for external applicants to apply. Should include:
+External applicants should complete an application form (link above). The form will require applicants to provide the following information:
   + Organisation (and whether student/staff)
   + Upload CV (qualifications and to confirm coding skills)
   + Link to Github profile
   + Short description of previous projects
   + Details of 1 referee
   + Short bio/personal statement on why they want to attend/what they hope to gain from the course
-  + Short test? Covering python knowledge and basic Bayesian inference
+
+Apllicants may also be required to complete a short test covering python knowledge and basic Bayesian inference.
 
 **Contact:** Dr Alexandra Blenkinsop (<a.blenkinsop@imperial.ac.uk>)
 

content/sa_aimsximperial2025/lecturers/_index.md

@@ -21,9 +21,9 @@
 
 
 <center>
-<img src="../resources/imperial.png" width="250" hspace="50" style="display:inline-block;margin:10px;"/>
+<img src="../resources/imperial.png" width="250" style="display:inline-block;margin:5px;"/>
 <img src="../resources/mlgh.png" width="200" hspace="50" style="display:inline-block;margin:50px;"/>
-<img src="../resources/ammi.png" width="200" style="display:inline-block;"/>
+<img src="../resources/ammi.png" width="200" style="display:inline-block;margin:-3px"/>
 </center>
 
 # Lecturers

content/sa_aimsximperial2025/overview/_index.md

@@ -45,17 +45,17 @@
 </style>
 
 <center>
-<img src="../resources/imperial.png" width="250" hspace="50" style="display:inline-block;margin:10px;"/>
+<img src="../resources/imperial.png" width="250" style="display:inline-block;margin:5px;"/>
 <img src="../resources/mlgh.png" width="200" hspace="50" style="display:inline-block;margin:50px;"/>
-<img src="../resources/ammi.png" width="200" style="display:inline-block;"/>
+<img src="../resources/ammi.png" width="200" style="display:inline-block;margin:-3px"/>
 </center>
 
 <br>
 <br>
 
 <div class="shift-up-title"></div>
 
-# AI and Probabilistic Programming for Global Health in Africa
+# Modern Statistics and Machine Learning for Population Health in Africa
 
 
 <div class="shift-up-img"></div>
@@ -64,7 +64,7 @@
 
 <div class="space"></div>
 
-### A hands-on course for students and researchers at the intersection of statistics and public health
+### A hands-on course for students and researchers at the intersection of statistics, probabilistic programaming, and population health
 
 **24th - 28th March 2025**
 <br/>
@@ -110,5 +110,5 @@ This one-week course will cover how you can integrate modern statistical techniq
 <center>
 <a href="https://mlgh.net/sa_aimsximperial2025/application/" class="button">Apply<a/>
 </center>
-
+<br>
 

content/sa_aimsximperial2025/programme/_index.md

@@ -11,14 +11,13 @@
 </style>
 
 <center>
-<img src="../resources/imperial.png" width="250" hspace="50" style="display:inline-block;margin:10px;"/>
+<img src="../resources/imperial.png" width="250" style="display:inline-block;margin:5px;"/>
 <img src="../resources/mlgh.png" width="200" hspace="50" style="display:inline-block;margin:50px;"/>
-<img src="../resources/ammi.png" width="200" style="display:inline-block;"/>
+<img src="../resources/ammi.png" width="200" style="display:inline-block;margin:-3px"/>
 </center>
 
 # Full programme
 
-
 #### 24 March, Day 1
 ***Refresher***
 1. Welcome: Introductions (9.00 - 9.30)
@@ -29,82 +28,82 @@
 
 4. Lecture: Statistical learning (11.00-12.00)
 
-5. Lecture: Intro to Stan  (12.00 - 12.30)
-
-6. Lunch (12.30 - 13.30)
+5. Lecture: Intro to Stan  (12.00 - 13:00)
 
-7. Lecture: Intro to Stan (continued) (13.30 - 14.00)
+6. Lunch (13.00 - 13.30)
 
-8. Hands-on: Introduction to statistical learning with Stan in python (14.00 - 16.00)
+7. Hands-on: Introduction to statistical learning with Stan in python (13.30 - 15.30)
 
+8. Recap session (15:30-16:00)
 
 #### 25 March, Day 2
 ***Scalable Gaussian process regression models in Stan***
-
-1. Recap session and Q&A in break-out rooms (max 10 ppl) (09.00 - 09.30)
+1. Q&A in break-out rooms (max 10 ppl) (09.00 - 09.30)
 
 2. Lecture: Intro to Gaussian processes (09.30-10.30)
 
 3. Break (10.30-11.00)
 
-4. Lecture: Scalable Gaussian process regression models in Stan (11.00-11.30)
+4. Lecture/hands-on: Scalable Gaussian process regression models in Stan (11.00-13.00)
 
-5. Lunch (12.30-13.30)
+5. Lunch (13.00-13.30)
 
-6. Inspirational Lecture: Two research talks from the Machine Learning and Global Health Network (13.30 - 14.30)
+6. Hands-on: Scalable Gaussian process regression models (13.30-14.30)
 
-7. Hands-on: Scalable Gaussian process regression models (14.00-16.00)
-
-8. Social: BBQ or similar (18.00 - 20.00)
+8. Inspirational Lecture: Two research talks from the Machine Learning and Global Health Network (14.30 - 15.30)
 
+9. Recap session (15:30-16:00)
 
 #### 26 March, Day 3
 ***Gaussian processes continued***
-
-1. Recap session and Q&A in break-out rooms (max 10 ppl) (09.00 - 09.30)
+1. Q&A in break-out rooms (max 10 ppl) (09.00 - 09.30)
 
 2. Lecture/Hands-on: Scalable Gaussian process regression models (09:30 – 10:30)
 
 3. Break (10.30-11.00)
 
-4. Group project (11.00 - 12.30)
+4. Group project analysing real-world datasets e.g. of malaria cases, spatial data on drought, HIV drug resistance (11.00 - 13:00)
 
-5. Lunch (12:30-13:30)
+5. Lunch (13:00-13:30)
 
 6. Group project continued (13.30 - 15.00)
 
 7. Groups present (15.00-16.00)
 
 #### 27 March, Day 4
 ***Infectious Disease Modelling with Stan***
-
-
 1. Lecture: Introduction to Infectious Disease Modelling and Compartmental Modelling (09.00-10:20)
 
 2. Break (10.20-10.50)
 
 3. Practical: Deriving simple SIR type models with pen and paper (10:50 – 11:30)
 
-4. Practical: SIR models in Stan (11.30-12.30)
-
-5. Lunch (12:30-13:30)
+4. Practical: SIR models in Stan (11.30-13:00)
 
-6. Inspirational Lecture: Local research talks (two-three) (13.30 - 14.30)
+5. Lunch (13:00-13:30)
 
-7. Practical: SIR models in Stan (continued) (14.30-16.00)
+7. Practical: SIR models in Stan (continued) (13.30-15.00)
 
+6. Inspirational Lecture: Local research talks (two-three) (15.00 - 16.00)
 
 #### 28 March, Day 5
 ***Phylogenetics***
+1. Recap session and Q&A in break-out rooms (max 10 ppl) (09.00 - 09.30)
+
+2. Lecture: Introduction to phylogenetics (09:30-10:30)
+
+3. Break (10.30-11.00)
+
+4. Practical: Running a phylogenetic pipeline (11:00-13:00)
 
-1. Lecture: Introduction to phylogenetics (09:00-10:30)
+5. Lunch (13:00-13:30)
 
-2. Break (10.30-11.00)
+6. Guided practical: More phylogenetics (13:30 – 14:30)
 
-3. Practical: Running a phylogenetic pipeline (11:00-12:30)
+7. Q&A (14:30 - 15:00)
 
-4. Lunch (12:30-13:30)
+8. Quiz (15:00 - 15:30)
 
-5. Guided practical: More phylogenetics (13:30 – 14:30)
+9. Introduce take-home assignment (15:30-16:00)
 
-6. Wrap-up (14:30 – 15:00)
+10. Social: BBQ or similar (18.00 - 20.00)

content/short_courses/upcoming/AIMSxImperial2025/index.md

@@ -1,6 +1,6 @@
 ---
-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.
+title:  Modern Statistics and Machine Learning for Population Health in Africa
+subtitle: A hands-on course for students and researchers at the intersection of statistics, probabilistic programaming, and population 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.
 
 lastmod: 2024-11-18