diff --git a/notebooks/01_Introduction.ipynb b/notebooks/01_Introduction.ipynb
index 0ef1a24..f9ceab4 100644
--- a/notebooks/01_Introduction.ipynb
+++ b/notebooks/01_Introduction.ipynb
@@ -10,7 +10,7 @@
    "source": [
     "# Exercises\n",
     "\n",
-    "Today's exercises are meant to allow you to get some initial familiarisation with the `mlp` package and how data is provided to the learning functions. You are going to implement variants of a `DataProvider` class, which preprocesses data and serves data in batches when the `__next__()` function is called. \n",
+    "Today's exercises are meant to allow you to get some initial familiarisation with the `mlp` package and how data is provided to the learning functions. You are going to implement variants of a `DataProvider` class, which preprocesses data and serves data in batches when the `next()` function is called. \n",
     "\n",
     "If you are new to Python and/or NumPy and are struggling to complete the exercises, you may find going through [this Stanford University tutorial](http://cs231n.github.io/python-numpy-tutorial/) by Justin Johnson first helps. There is also a derived Jupyter notebook by Volodymyr Kuleshov and Isaac Caswell which you can download [from here](https://github.com/kuleshov/teaching-material/blob/master/tutorials/python/cs228-python-tutorial.ipynb) - if you save this in to your `mlpractical/notebooks` directory you should be able to open the notebook from the dashboard to run the examples.\n",
     "\n",