From d155d6af08706e940fe9a67bb606292720ecc219 Mon Sep 17 00:00:00 2001
From: "Sterling G. Baird" <sterling.baird@utah.edu>
Date: Tue, 14 Nov 2023 01:08:05 -0500
Subject: [PATCH] Update index.md

---
 docs/index.md | 24 +++++++++++++++++-------
 1 file changed, 17 insertions(+), 7 deletions(-)

diff --git a/docs/index.md b/docs/index.md
index 809796f..ec63283 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -1,6 +1,16 @@
 # 📜 Autonomous Systems for Discovery Certificate
 
-While advanced materials hold the potential to improve our lives and our world, conventional methods of discovery are slow and expensive. "Self-driving" (i.e., autonomous) laboratories have the power to radically fast-track materials discovery—from an average of 20 years and \$100 million to as little as 1 year and \$1 million. This paradigm shift requires highly qualified personnel and multidisciplinary expertise. While extensive degree-based training can provide deep expertise in a single field, formal education options which provide needed cross-disciplinary skills are sparse. The *Autonomous Systems for Discovery* certificate will address this gap with a set of microcourses that introduces self-driving labs, provides deeper dives into data science, robotics, and software development, and facilitates a capstone project. Each course will contain a series of hands-on guided tutorials and coding exercises for participants to adapt and apply what they've learned. This certificate will provide familiarity with the terminology, principles, and tools required for the highly interdisciplinary teams necessary to build state-of-the-art self-driving labs. While the certificate option requires formal registration and tuition dues, the course content is made freely available. <!-- Alan's YouTube video, either here or as part of the Hello, World! course -->
+```{warning}
+This project is currently under development and the official microcredentials courses are not live. If you would like to participate or are interested in contributing, please [introduce yourself and join the discussion](https://github.com/AccelerationConsortium/ac-microcourses/discussions/2).
+```
+
+While advanced materials hold the potential to improve our lives and our world, conventional methods of discovery are slow and expensive. "Self-driving" (i.e., autonomous) laboratories have the power to radically fast-track materials discovery—from an average of 20 years and \$100 million to as little as 1 year and \$1 million. This paradigm shift requires highly qualified personnel and multidisciplinary expertise. While extensive degree-based training can provide deep expertise in a single field, formal education options which provide needed cross-disciplinary skills are sparse. The *Autonomous Systems for Discovery* certificate addresses this gap with a set of microcourses that introduces self-driving labs, provides deeper dives into data science, robotics, and software development, and facilitates a capstone project. Each course contains a series of hands-on guided tutorials and coding exercises for participants to adapt and apply what they've learned. This certificate will provide familiarity with the terminology, principles, and tools required for the highly interdisciplinary teams necessary to build state-of-the-art self-driving labs.
+
+```{note}
+While the certificate option requires formal registration and tuition dues, the course content is made freely available.
+```
+
+<!-- Alan's YouTube video, either here or as part of the Hello, World! course -->
 <!-- description of the microcredentials, and the difference between the microcourse content and the microcredentials certificate -->
 
 <!-- In the first course, participants will design and build a "Hello World" for self-driving labs using physical hardware and Python programming. The next three courses provide deeper dives into data science, robotics, and software development topics. These courses  will enable participants to iteratively suggest the next best experiment to perform, use a database backend to programatically upload and retrieve materials data, and orchestrate experimental and computational workflows. Likewise, participants will use software development tools and best practices to maximize efficiency and minimize frustration. The fifth and final course is a capstone project conducted in-person at the AC training lab, where participants will have access to both educational and research-grade equipment. -->
@@ -36,11 +46,11 @@ While the first four courses are fully remote and asychronous, the final capston
 
 Upon completion of this certificate, you will be able to:
 
-1. Recreate a color-matching self-driving lab from scratch using a LEDs, a microcontroller, and a light sensor
-1. Write Python scripts that use AI to iteratively suggest next experiments for advanced optimization tasks and store to a database
-1. Write Python scripts to control robots and orchestrate experimental and computational workflows
-1. Leverage state-of-the-art software development tools and implement best practices
-1. Develop, defend, and execute a project proposal for a self-driving lab
+1. 💡 Recreate a color-matching self-driving lab from scratch using a LEDs, a microcontroller, and a light sensor
+1. 📈 Write Python scripts that use AI to iteratively suggest next experiments for advanced optimization tasks and store to a database
+1. 🦾 Write Python scripts to control robots and orchestrate experimental and computational workflows
+1. 🧑‍💻 Leverage state-of-the-art software development tools and implement best practices
+1. 🏢 Develop, defend, and execute a project proposal for a self-driving lab
 
 <!-- 1. Use a database backend to programatically upload and retrieve materials data -->
 
@@ -49,7 +59,7 @@ Explore the course-level modules, topics, and learning outcomes with the links b
 ```{toctree}
 :maxdepth: 2
 
-Framework <certificate-framework>
+Microcourse Details <certificate-framework>
 ```
 
 <!-- Perhaps use nested <details> to keep the content all within the index page -->