diff --git a/examples/notebooks/Getting Started/plotting_a_dataset.ipynb b/examples/notebooks/Getting Started/plotting_a_dataset.ipynb
index 633388374..56947a286 100644
--- a/examples/notebooks/Getting Started/plotting_a_dataset.ipynb	
+++ b/examples/notebooks/Getting Started/plotting_a_dataset.ipynb	
@@ -1,5 +1,14 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Setting up the Environment\n",
+    "\n",
+    "Before we begin, we need to ensure that we have all the necessary tools. We will install PyBOP from its development branch and upgrade some dependencies:"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 7,
@@ -19,6 +28,13 @@
     "%pip install git+https://github.com/pybop-team/PyBOP.git@develop -q"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next, we import the added packages plus any additional dependencies,"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 8,
@@ -31,6 +47,14 @@
     "import pybop\n"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Optimising the Parameters\n",
+    "First, we define the model to be used for the parameter optimisation,"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 9,
@@ -42,14 +66,38 @@
     "parameter_set = pybamm.get_size_distribution_parameters(parameter_set)\n",
     "synth_model = pybop.lithium_ion.DFN(\n",
     "    parameter_set=parameter_set, options={\"particle size\": \"distribution\"}\n",
-    ")\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Simulating Forward Model\n",
     "\n",
+    "We can then simulate the model using the `predict` method, with a default constant current to generate voltage data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "n_points = 650\n",
     "t_eval = np.linspace(0, 1600 + 1000, n_points)\n",
     "current = np.concatenate(\n",
     "    [np.ones(400) * parameter_set[\"Nominal cell capacity [A.h]\"], np.zeros(250)]\n",
     ")\n",
-    "init_soc = 0.5\n",
+    "init_soc = 0.5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "dataset = pybop.Dataset(\n",
     "    {\n",
     "        \"Time [s]\": t_eval,\n",
@@ -57,7 +105,15 @@
     "    }\n",
     ")\n",
     "synth_model.build(dataset, init_soc=init_soc)\n",
-    "synth_model.signal = [\"Voltage [V]\"]\n"
+    "synth_model.signal = [\"Voltage [V]\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plotting the Dataset\n",
+    "The `pybop.plot_dataset` function is used to visualize the dataset, showing the voltage over time."
    ]
   },
   {