Merge pull request #8 from zabore/main

adding hannah workshop

docs/search.json

@@ -4,14 +4,21 @@
     "href": "workshops.html#personal-r-administration",
     "title": "R/Medicine 2025",
     "section": "Personal R Administration",
-    "text": "Personal R Administration\n\nDavid Aja and Shannon Pileggi\n \n\n\nDescription\n\nDoes the release of a new R version fill you with dread?\nAre there passwords in your R code?\nDo you look at the output of a failed package installation and think to yourself, “WTF?!”\n\nIf you said yes to any of those questions, then you need Personal R Administration. You’ll come away with tips, tricks, tweaks, and some hacks for building data science dev environments that you won’t be afraid to come back to in a year.\n\n\nBiographies\nE. David Aja is a Software Engineer at Posit. Before joining Posit, he worked as a data scientist in the public sector.\nShannon Pileggi (she/her) is a Lead Data Scientist at The Prostate Cancer Clinical Trials Consortium, a frequent blogger, and a member of the R-Ladies Global leadership team. She enjoys automating data wrangling and data outputs, and making both data insights and learning new material digestible."
+    "text": "Personal R Administration\n\n\n\nDescription\n\nDoes the release of a new R version fill you with dread?\nAre there passwords in your R code?\nDo you look at the output of a failed package installation and think to yourself, “WTF?!”\n\nIf you said yes to any of those questions, then you need Personal R Administration. You’ll come away with tips, tricks, tweaks, and some hacks for building data science dev environments that you won’t be afraid to come back to in a year.\n\n\n\n\n\nDavid Aja and Shannon Pileggi\n \nE. David Aja is a Software Engineer at Posit. Before joining Posit, he worked as a data scientist in the public sector.\nShannon Pileggi (she/her) is a Lead Data Scientist at The Prostate Cancer Clinical Trials Consortium, a frequent blogger, and a member of the R-Ladies Global leadership team. She enjoys automating data wrangling and data outputs, and making both data insights and learning new material digestible."
   },
   {
     "objectID": "workshops.html#teal-mastery-from-pre-built-modules-to-custom-module-creation",
     "href": "workshops.html#teal-mastery-from-pre-built-modules-to-custom-module-creation",
     "title": "R/Medicine 2025",
     "section": "teal Mastery: From Pre-built Modules to Custom Module Creation",
-    "text": "teal Mastery: From Pre-built Modules to Custom Module Creation\n\nDony Unardi\n\n\n\nDescription\nThis session provides a comprehensive introduction to teal programming, starting with creating a simple teal application from scratch. You’ll learn the fundamentals of building a basic teal app and understand its core components. Next, we will explore the practical use of pre-built modules from teal.modules.general and teal.modules.clinical, demonstrating how these ready-to-use components can streamline the development of robust teal applications. Participants will gain hands-on experience in integrating these modules into their projects. The workshop will then focus on building upon this foundation by learning how to create custom teal modules that meet specific project needs. You’ll learn how to leverage the core features of the teal framework to develop tailored solutions and take your skills to the next level. This session will provide practical insights and coding examples, empowering you to extend and customize your teal applications beyond the capabilities of pre-built modules. By the end of this workshop, you will have a comprehensive understanding of both pre-built and custom module development in teal, making it an ideal choice for beginners and intermediate learners looking to expand their R skills with teal.\n\n\nBiography\nDony Unardi is a Principal Data Scientist at Genentech, and the Engineering Team Lead in the development effort of an open-source R product called teal, a Shiny-based R package focused on interactive and reproducible data analysis and visualization in clinical trials."
+    "text": "teal Mastery: From Pre-built Modules to Custom Module Creation\n\n\n\nDescription\nThis session provides a comprehensive introduction to teal programming, starting with creating a simple teal application from scratch. You’ll learn the fundamentals of building a basic teal app and understand its core components. Next, we will explore the practical use of pre-built modules from teal.modules.general and teal.modules.clinical, demonstrating how these ready-to-use components can streamline the development of robust teal applications. Participants will gain hands-on experience in integrating these modules into their projects. The workshop will then focus on building upon this foundation by learning how to create custom teal modules that meet specific project needs. You’ll learn how to leverage the core features of the teal framework to develop tailored solutions and take your skills to the next level. This session will provide practical insights and coding examples, empowering you to extend and customize your teal applications beyond the capabilities of pre-built modules. By the end of this workshop, you will have a comprehensive understanding of both pre-built and custom module development in teal, making it an ideal choice for beginners and intermediate learners looking to expand their R skills with teal.\n\n\n\n\n\nDony Unardi\n\nDony Unardi is a Principal Data Scientist at Genentech, and the Engineering Team Lead in the development effort of an open-source R product called teal, a Shiny-based R package focused on interactive and reproducible data analysis and visualization in clinical trials."
+  },
+  {
+    "objectID": "workshops.html#survival-analysis-with-tidymodels",
+    "href": "workshops.html#survival-analysis-with-tidymodels",
+    "title": "R/Medicine 2025",
+    "section": "Survival analysis with tidymodels",
+    "text": "Survival analysis with tidymodels\n\n\n\nDescription\nSurvival analysis is now supported across the tidymodels framework, a collection of R packages for modeling and machine learning using tidyverse principles. It covers the entire predictive modeling workflow from data splitting, resampling, feature engineering, model fitting, and performance evaluation to tuning. It provides a consistent interface with composable functions that allow beginners a safe start and advanced users access to more specialized techniques such as feature engineering on text data or tuning via racing methods. The addition of dedicated performance metrics has enabled us to support tuning of survival models and unlock the entire framework for survival analysis. This workshop focuses on the core components of tidymodels to get you up and running with predictive survival analysis.\nThis workshop is for you if you\n\nare familiar with basic survival analysis such as censoring of time-to-event data, Kaplan-Meier curves, proportional hazards models\nare familiar with the basic predictive modeling workflow such as split in train and test set, resampling, tuning via grid search\nwant to learn how to leverage the tidymodels framework for survival analysis\n\n\n\n\n\n\nHannah Frick\n\nHannah Frick is a software engineer on the tidymodels team at Posit. She holds a PhD in statistics and has worked in interdisciplinary research and data science consultancy. She is a co-founder of R-Ladies Global."
   },
   {
     "objectID": "Register.html",

docs/workshops.html

@@ -145,6 +145,9 @@ <h2 id="toc-title">On this page</h2>
 
   <ul>
   <li><a href="#workshops" id="toc-workshops" class="nav-link active" data-scroll-target="#workshops">Workshops</a></li>
+  <li><a href="#personal-r-administration" id="toc-personal-r-administration" class="nav-link" data-scroll-target="#personal-r-administration">Personal R Administration</a></li>
+  <li><a href="#teal-mastery-from-pre-built-modules-to-custom-module-creation" id="toc-teal-mastery-from-pre-built-modules-to-custom-module-creation" class="nav-link" data-scroll-target="#teal-mastery-from-pre-built-modules-to-custom-module-creation">teal Mastery: From Pre-built Modules to Custom Module Creation</a></li>
+  <li><a href="#survival-analysis-with-tidymodels" id="toc-survival-analysis-with-tidymodels" class="nav-link" data-scroll-target="#survival-analysis-with-tidymodels">Survival analysis with tidymodels</a></li>
   </ul>
 </nav>
     </div>
@@ -157,14 +160,10 @@ <h2 id="toc-title">On this page</h2>
 <section id="workshops" class="level2">
 <h2 class="anchored" data-anchor-id="workshops">Workshops</h2>
 </section>
-<div class="columns">
-<div class="column" style="width:45%;">
 <section id="personal-r-administration" class="level2">
 <h2 class="anchored" data-anchor-id="personal-r-administration">Personal R Administration</h2>
-<section id="david-aja-and-shannon-pileggi" class="level3">
-<h3 class="anchored" data-anchor-id="david-aja-and-shannon-pileggi">David Aja and Shannon Pileggi</h3>
-<p><img src="images/david-aja.jpg" class="img-fluid"> <img src="images/Shannon_small.jpg" class="img-fluid"></p>
-</section>
+<div class="columns">
+<div class="column" style="width:45%;">
 <section id="description" class="level3">
 <h3 class="anchored" data-anchor-id="description">Description</h3>
 <ul>
@@ -174,34 +173,64 @@ <h3 class="anchored" data-anchor-id="description">Description</h3>
 </ul>
 <p>If you said yes to any of those questions, then you need Personal R Administration. You’ll come away with tips, tricks, tweaks, and some hacks for building data science dev environments that you won’t be afraid to come back to in a year.</p>
 </section>
-<section id="biographies" class="level3">
-<h3 class="anchored" data-anchor-id="biographies">Biographies</h3>
+</div><div class="column" style="width:10%;">
+<!-- empty column to create gap -->
+</div><div class="column" style="width:45%;">
+<section id="david-aja-and-shannon-pileggi" class="level3">
+<h3 class="anchored" data-anchor-id="david-aja-and-shannon-pileggi">David Aja and Shannon Pileggi</h3>
+<p><img src="images/david-aja.jpg" class="img-fluid"> <img src="images/Shannon_small.jpg" class="img-fluid"></p>
 <p>E. David Aja is a Software Engineer at Posit. Before joining Posit, he worked as a data scientist in the public sector.</p>
 <p><a href="https://www.pipinghotdata.com/">Shannon Pileggi</a> (she/her) is a Lead Data Scientist at The Prostate Cancer Clinical Trials Consortium, a frequent blogger, and a member of the R-Ladies Global leadership team. She enjoys automating data wrangling and data outputs, and making both data insights and learning new material digestible.</p>
 </section>
+</div>
+</div>
+</section>
+<section id="teal-mastery-from-pre-built-modules-to-custom-module-creation" class="level2">
+<h2 class="anchored" data-anchor-id="teal-mastery-from-pre-built-modules-to-custom-module-creation">teal Mastery: From Pre-built Modules to Custom Module Creation</h2>
+<div class="columns">
+<div class="column" style="width:45%;">
+<section id="description-1" class="level3">
+<h3 class="anchored" data-anchor-id="description-1">Description</h3>
+<p>This session provides a comprehensive introduction to teal programming, starting with creating a simple teal application from scratch. You’ll learn the fundamentals of building a basic teal app and understand its core components. Next, we will explore the practical use of pre-built modules from teal.modules.general and teal.modules.clinical, demonstrating how these ready-to-use components can streamline the development of robust teal applications. Participants will gain hands-on experience in integrating these modules into their projects. The workshop will then focus on building upon this foundation by learning how to create custom teal modules that meet specific project needs. You’ll learn how to leverage the core features of the teal framework to develop tailored solutions and take your skills to the next level. This session will provide practical insights and coding examples, empowering you to extend and customize your teal applications beyond the capabilities of pre-built modules. By the end of this workshop, you will have a comprehensive understanding of both pre-built and custom module development in teal, making it an ideal choice for beginners and intermediate learners looking to expand their R skills with teal.</p>
 </section>
 </div><div class="column" style="width:10%;">
 <!-- empty column to create gap -->
 </div><div class="column" style="width:45%;">
-<section id="teal-mastery-from-pre-built-modules-to-custom-module-creation" class="level2">
-<h2 class="anchored" data-anchor-id="teal-mastery-from-pre-built-modules-to-custom-module-creation">teal Mastery: From Pre-built Modules to Custom Module Creation</h2>
 <section id="dony-unardi" class="level3">
 <h3 class="anchored" data-anchor-id="dony-unardi">Dony Unardi</h3>
 <p><img src="images/dony.png" class="img-fluid"></p>
+<p>Dony Unardi is a Principal Data Scientist at Genentech, and the Engineering Team Lead in the development effort of an open-source R product called teal, a Shiny-based R package focused on interactive and reproducible data analysis and visualization in clinical trials.</p>
 </section>
-<section id="description-1" class="level3">
-<h3 class="anchored" data-anchor-id="description-1">Description</h3>
-<p>This session provides a comprehensive introduction to teal programming, starting with creating a simple teal application from scratch. You’ll learn the fundamentals of building a basic teal app and understand its core components. Next, we will explore the practical use of pre-built modules from teal.modules.general and teal.modules.clinical, demonstrating how these ready-to-use components can streamline the development of robust teal applications. Participants will gain hands-on experience in integrating these modules into their projects. The workshop will then focus on building upon this foundation by learning how to create custom teal modules that meet specific project needs. You’ll learn how to leverage the core features of the teal framework to develop tailored solutions and take your skills to the next level. This session will provide practical insights and coding examples, empowering you to extend and customize your teal applications beyond the capabilities of pre-built modules. By the end of this workshop, you will have a comprehensive understanding of both pre-built and custom module development in teal, making it an ideal choice for beginners and intermediate learners looking to expand their R skills with teal.</p>
+</div>
+</div>
 </section>
-<section id="biography" class="level3">
-<h3 class="anchored" data-anchor-id="biography">Biography</h3>
-<p>Dony Unardi is a Principal Data Scientist at Genentech, and the Engineering Team Lead in the development effort of an open-source R product called teal, a Shiny-based R package focused on interactive and reproducible data analysis and visualization in clinical trials.</p>
+<section id="survival-analysis-with-tidymodels" class="level2">
+<h2 class="anchored" data-anchor-id="survival-analysis-with-tidymodels">Survival analysis with tidymodels</h2>
+<div class="columns">
+<div class="column" style="width:45%;">
+<section id="description-2" class="level3">
+<h3 class="anchored" data-anchor-id="description-2">Description</h3>
+<p>Survival analysis is now supported across the tidymodels framework, a collection of R packages for modeling and machine learning using tidyverse principles. It covers the entire predictive modeling workflow from data splitting, resampling, feature engineering, model fitting, and performance evaluation to tuning. It provides a consistent interface with composable functions that allow beginners a safe start and advanced users access to more specialized techniques such as feature engineering on text data or tuning via racing methods. The addition of dedicated performance metrics has enabled us to support tuning of survival models and unlock the entire framework for survival analysis. This workshop focuses on the core components of tidymodels to get you up and running with predictive survival analysis.</p>
+<p>This workshop is for you if you</p>
+<ul>
+<li>are familiar with basic survival analysis such as censoring of time-to-event data, Kaplan-Meier curves, proportional hazards models</li>
+<li>are familiar with the basic predictive modeling workflow such as split in train and test set, resampling, tuning via grid search</li>
+<li>want to learn how to leverage the tidymodels framework for survival analysis</li>
+</ul>
 </section>
+</div><div class="column" style="width:10%;">
+<!-- empty column to create gap -->
+</div><div class="column" style="width:45%;">
+<section id="hannah-frick" class="level3">
+<h3 class="anchored" data-anchor-id="hannah-frick">Hannah Frick</h3>
+<p><img src="images/frick.jpeg" class="img-fluid"></p>
+<p>Hannah Frick is a software engineer on the tidymodels team at Posit. She holds a PhD in statistics and has worked in interdisciplinary research and data science consultancy. She is a co-founder of R-Ladies Global.</p>
 </section>
 </div>
 </div>
 
 
+</section>
 
 </main> <!-- /main -->
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