diff --git a/notebooks/01_Introduction.ipynb b/notebooks/01_Introduction.ipynb
index 3dd0f49..5ca89ca 100644
--- a/notebooks/01_Introduction.ipynb
+++ b/notebooks/01_Introduction.ipynb
@@ -256,7 +256,7 @@
     "\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. Next week onwards, we will follow with the material covered in lectures. \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/) first helps. There is also a derived Jupyter notebook which you can download [from here](https://github.com/kuleshov/cs228-material/raw/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",
+    "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](http://cs.stanford.edu/people/jcjohns/) first helps. There is also a derived Jupyter notebook by [Volodymyr Kuleshov](http://web.stanford.edu/~kuleshov/) and [Isaac Caswell](https://symsys.stanford.edu/viewing/symsysaffiliate/21335) which you can download [from here](https://github.com/kuleshov/cs228-material/raw/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",
     "## Data providers\n",
     "\n",