diff --git a/.gitignore b/.gitignore
index e64627a3d..be030005f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -5,6 +5,9 @@
 
 dist 
 
+#pythion virtual envs
+venv*
+
 # User-specific files
 *.rsuser
 *.suo
diff --git a/1-Introduction/3-fairness/DanNotes.txt.bak b/1-Introduction/3-fairness/DanNotes.txt.bak
new file mode 100644
index 000000000..e69de29bb
diff --git a/1-Introduction/4-techniques-of-ML/DanNotes.txt b/1-Introduction/4-techniques-of-ML/DanNotes.txt
new file mode 100644
index 000000000..124166c9d
--- /dev/null
+++ b/1-Introduction/4-techniques-of-ML/DanNotes.txt
@@ -0,0 +1,14 @@
+- Decide is AI is the right approcahc for your problem
+    - if the problem can be solved with a well defined set of rules -> not AI
+    - plenty of data with useful information about your problem -> AI
+- Collect and prepare your data
+    - cleanup, format, eliminate rows or fields
+    - choose features that you will use as input for predictions (suh as medical history) 
+    - choose what you will predict - probability for a disease
+    - split into training data and test data, say 80% to 20%
+- Train your model
+    - chose algorithms or use them all.
+- Evaluate your model
+- Tuning the model's hyperparameters
+- Testing the trained model in the real-world
+
diff --git a/2-Regression/1-Tools/DanNotes.txt b/2-Regression/1-Tools/DanNotes.txt
new file mode 100644
index 000000000..e69de29bb
diff --git a/2-Regression/1-Tools/notebook.ipynb b/2-Regression/1-Tools/notebook.ipynb
index e69de29bb..f0c3292fb 100644
--- a/2-Regression/1-Tools/notebook.ipynb
+++ b/2-Regression/1-Tools/notebook.ipynb
@@ -0,0 +1,31 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# My first notebook"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "plaintext"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "print(\"Hello, world from python notebook\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}