Starting tutortial with 1. Theory 2. Engineering and 3. Code

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diff --git a/tutorials/module_3/numerical_differentiation.ipynb b/tutorials/module_3/numerical_differentiation.ipynb
index f8091d0..a24a46f 100644
--- a/tutorials/module_3/numerical_differentiation.ipynb
+++ b/tutorials/module_3/numerical_differentiation.ipynb
@@ -6,6 +6,15 @@
    "metadata": {},
    "source": [
     "# Numerical Differentiation\n",
+    "WHAT IS IT?\n",
+    "Numerical Differentiation is a way we can use \n",
+    "\n",
+    "WHAT IS A DERIVATIVE?\n",
+    "\n",
+    "\n",
+    "HOW CAN WE CALCULATE IT?\n",
+    "\n",
+    "\n",
     "We can find the derivate of both tabulated data and a continuous function using a finite difference method, which calculates rise over run of a function. To do this, we must first initalize our independant variable. Let's call this domain $x$ to be a vector such that $\\vec{x}$ =\n",
     "$\\pmatrix{x_0, x_1, x_2, ...}$. This domain is also known as the **numerical grid**, is either determined by our data (often time) or can be set by us if it's a continuous function. The **step size** is defined as the spacing between adjacent points on the grid ($h = x_{i+1} - x_i$). Next, let's introduce the dependent variable $y$, this can be any function of $x$.\n",
     "\n",
@@ -41,6 +50,7 @@
    "id": "9b79e5ba-4b71-4aeb-b3fb-878c2d728f7e",
    "metadata": {},
    "source": [
+    "---\n",
     "## Forward Difference\n",
     "The forward difference method takes the point at which we want to find the derivative and the point *forwards* on the grid.\n",
     "\n",