diff --git a/intro-to-pytorch/Part 7 - Loading Image Data (Exercises).ipynb b/intro-to-pytorch/Part 7 - Loading Image Data (Exercises).ipynb
index e4cbb8ff40..c6e040d110 100644
--- a/intro-to-pytorch/Part 7 - Loading Image Data (Exercises).ipynb	
+++ b/intro-to-pytorch/Part 7 - Loading Image Data (Exercises).ipynb	
@@ -39,7 +39,7 @@
     "The easiest way to load image data is with `datasets.ImageFolder` from `torchvision` ([documentation](http://pytorch.org/docs/master/torchvision/datasets.html#imagefolder)). In general you'll use `ImageFolder` like so:\n",
     "\n",
     "```python\n",
-    "dataset = datasets.ImageFolder('path/to/data', transform=transforms)\n",
+    "dataset = datasets.ImageFolder('path/to/data', transform=transform)\n",
     "```\n",
     "\n",
     "where `'path/to/data'` is the file path to the data directory and `transforms` is a list of processing steps built with the [`transforms`](http://pytorch.org/docs/master/torchvision/transforms.html) module from `torchvision`. ImageFolder expects the files and directories to be constructed like so:\n",
@@ -98,7 +98,7 @@
    "source": [
     "data_dir = 'Cat_Dog_data/train'\n",
     "\n",
-    "transforms = # TODO: compose transforms here\n",
+    "transform = # TODO: compose transforms here\n",
     "dataset = # TODO: create the ImageFolder\n",
     "dataloader = # TODO: use the ImageFolder dataset to create the DataLoader"
    ]