add more lessons and first attempt at step 10

config.yaml

@@ -57,6 +57,10 @@ contact: '[email protected]'
 episodes:
 - introduction.md
 - problem-definition.md
+- scientific-validity.md
+- fairness.md
+- explainability.md
+- releasing-a-model.md
 
 # Information for Learners
 learners: 

episodes/explainability.md

@@ -0,0 +1,17 @@
+---
+title: "Explainability"
+teaching: 0
+exercises: 0
+---
+
+:::::::::::::::::::::::::::::::::::::: questions 
+
+- TODO
+
+::::::::::::::::::::::::::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::: objectives
+
+- TODO
+
+::::::::::::::::::::::::::::::::::::::::::::::::

episodes/fairness.md

@@ -0,0 +1,19 @@
+---
+title: "Fairness"
+teaching: 0
+exercises: 0
+---
+
+:::::::::::::::::::::::::::::::::::::: questions 
+
+- TODO
+
+::::::::::::::::::::::::::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::: objectives
+
+- Participants will be able to define and differntiate between various notions of fairness in the context of machine learning. 
+- Participants will be able to define (and implement?) two different ways of modifying the machine learning modeling process to improve the fairness of a model.
+- Participants will understand the limitations of fairness as a metric for machine learning models.
+
+::::::::::::::::::::::::::::::::::::::::::::::::

episodes/introduction.md

@@ -1,5 +1,5 @@
 ---
-title: "Using Markdown"
+title: "Introduction"
 teaching: 10
 exercises: 2
 ---

episodes/problem-definition.md

@@ -1,5 +1,5 @@
 ---
-title: "Problem definition"
+title: "Preparing to train a model"
 teaching: 0
 exercises: 0
 ---

episodes/releasing-a-model.md

@@ -0,0 +1,17 @@
+---
+title: "Releasing a model"
+teaching: 0
+exercises: 0
+---
+
+:::::::::::::::::::::::::::::::::::::: questions 
+
+- TODO
+
+::::::::::::::::::::::::::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::: objectives
+
+- TODO
+
+::::::::::::::::::::::::::::::::::::::::::::::::

episodes/scientific-validity.md

@@ -0,0 +1,17 @@
+---
+title: "Scientific Validity in the Modeling Process"
+teaching: 0
+exercises: 0
+---
+
+:::::::::::::::::::::::::::::::::::::: questions 
+
+- TODO
+
+::::::::::::::::::::::::::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::: objectives
+
+- TODO
+
+::::::::::::::::::::::::::::::::::::::::::::::::

index.md

@@ -4,11 +4,14 @@ site: sandpaper::sandpaper_site
 
 This lesson aims to teach responsible machine learning practices with a focus on fairness, explainability, and reproducibility.
 
-Prerequisites
+:::::::::: prereq
 - Participants should have experience using Python. 
 - Participants should have a basic understanding of machine learning (e.g., familiar with the concepts like train/test split and cross-validation) and should have trained at least one model in the past.
 - Participants should care about the interpretability, reproducibility, and/or fairness of the models they build.
 - Participants should have domain knowledge of the field they work in and want to build models for.
+::::::::::::::::
+
+
 
 [workbench]: https://carpentries.github.io/sandpaper-docs