diff --git a/.github/workflows/build-book-pullrequest.yaml b/.github/workflows/build-book-pullrequest.yaml
index 0de5ab90b..461e2a6d1 100644
--- a/.github/workflows/build-book-pullrequest.yaml
+++ b/.github/workflows/build-book-pullrequest.yaml
@@ -28,7 +28,7 @@ permissions:
   contents: read
 
 env:
-  DOCKER_TAG: pr_104
+  DOCKER_TAG: pr_107
 
 jobs:
   build-book:
diff --git a/.github/workflows/build-book.yaml b/.github/workflows/build-book.yaml
index 3166035cf..c620ddc9d 100644
--- a/.github/workflows/build-book.yaml
+++ b/.github/workflows/build-book.yaml
@@ -25,7 +25,7 @@ on:
         type: string  # had a lot of trouble with boolean types, see https://github.com/actions/runner/issues/1483
 
 env:
-  DOCKER_TAG: pr_104
+  DOCKER_TAG: pr_107
 
 jobs:
   build-container:
diff --git a/binder/Dockerfile b/binder/Dockerfile
index d09936008..ce2f163d0 100644
--- a/binder/Dockerfile
+++ b/binder/Dockerfile
@@ -1 +1 @@
-FROM ghcr.io/openradar/erad2024:pr_104
+FROM ghcr.io/openradar/erad2024:pr_107
diff --git a/myst.yml b/myst.yml
index ed40ece75..ebc21f0aa 100755
--- a/myst.yml
+++ b/myst.yml
@@ -76,13 +76,13 @@ project:
         - title: LROSE
           children:
             - file: notebooks/lrose/LROSE_Basics.ipynb
-            - file: notebooks/lrose/DD_Tornado_ERAD24.ipynb
-
             - file: notebooks/lrose/testing/stress_testing.ipynb
     - title: Project Workflows
       children:
+        - file: projects.md
         - title: LROSE & PyDDA multi doppler analysis
           children:
+            - file: notebooks/lrose/DD_Tornado_ERAD24.ipynb
             - file: notebooks/Retrieving_winds_with_pydda.ipynb
             - file: notebooks/lrose/LROSE_ERAD_fractl_samurai.ipynb
         - title: ARCO Radar Datasets
@@ -105,7 +105,6 @@ project:
     output_matplotlib_strings: remove
 site:
   options:
-    favicon: notebooks/images/icons/favicon.ico
     logo: notebooks/images/logos/erad_white_background.png
     logo_dark: notebooks/images/logos/erad_white_background.png
   nav:
diff --git a/notebooks/lrose/DD_Tornado_ERAD24.ipynb b/notebooks/lrose/DD_Tornado_ERAD24.ipynb
index 9cb9b7183..416b4de3b 100644
--- a/notebooks/lrose/DD_Tornado_ERAD24.ipynb
+++ b/notebooks/lrose/DD_Tornado_ERAD24.ipynb
@@ -5,7 +5,7 @@
    "id": "0",
    "metadata": {},
    "source": [
-    "# MULTI DOPPLER ANALYSIS \n",
+    "# Introduction to Multidoppler Analysis\n",
     "## COURSE: Open Radar - Open Source Software Tools for Radar Data Processing \n",
     "### ERAD - Rome, 9-13 September 2024\n",
     "\n",
diff --git a/projects.md b/projects.md
new file mode 100644
index 000000000..54abeae42
--- /dev/null
+++ b/projects.md
@@ -0,0 +1,14 @@
+# Projects Overview
+
+## [Wind Retrievals over Complex Terrain with LROSE and PyDDA](notebooks/lrose/DD_Tornado_ERAD24.ipynb)
+Within this project, students will use LROSE wind tools and PyDDA to derive 3-dimensional wind retrievals over complex terrain across Europe and beyond.
+
+## [Spaceborne / Ground Radar Comparison with GPM-API, xradar and wradlib](notebooks/gpm-api/SR_GR_Calibration_Applied.ipynb)
+Students will compare spaceborne radar data, from the Global Preciptiation Measurement (GPM) suite of instruments, to ground radar across Italy. They will use a suite of openradar tools to complete this comparison.
+
+## [Creating analysis-ready data with xradar with Quasi-Vertical Profiles (QVPs)](notebooks/Analysis-Ready/ARCO-Datasets.ipynb)
+In this project, students will demonstrate how utilizing radar data in the Analysis-Ready Cloud-Optimized (ARCO) format enables efficient computation of Quantitative Precipitation Estimates (QPE) and Quasi-Vertical Profiles (QVP). The ARCO format ensures that radar data is pre-processed, clean, and well-organized, significantly reducing the time spent on data preparation and cleaning.
+
+## [Quantative Precipitation Estimation (QPE) in Northern Italy](notebooks/pyrad/description-pyrad-tutorial.ipynb)
+
+In this project we will learn how to setup a data processing chain for radar rainfall rate retrieval. The project will show the main steps involved between reading raw polarimetric moments to comparing rainfall rate retrievals with rain gauges, including clutter filtering, PhiDP estimation, KDP retrieval, etc. During the course, the processing chain implementation will be performed with [Pyrad](https://github.com/meteoswiss/pyrad). Examples of how to implement a processing chain using other available software packages will be provided as post-course material.
\ No newline at end of file