diff --git a/ML-Coursework_Complete.ipynb b/ML-Coursework_Complete.ipynb
index 620f88e..0ed5f39 100644
--- a/ML-Coursework_Complete.ipynb
+++ b/ML-Coursework_Complete.ipynb
@@ -1906,7 +1906,7 @@
     "2. `pool_1` is max pooling layer with a 2x2 window with a stride of 2 (use [`tf.layers.max_pooling2d`](https://www.tensorflow.org/api_docs/python/tf/layers/max_pooling2d))\n",
     "3. `conv_2` is 16 filters with a 5x5 kernel size and stride of 1, ReLU activation\n",
     "4. `pool_2` is max pooling layer with a 2x2 window with a stride of 2\n",
-    "5. `conv_3` is 125 filters with a 1x1 kernel size and stride of 1, ReLU activation\n",
+    "5. `conv_3` is 120 filters with a 1x1 kernel size and stride of 1, ReLU activation\n",
     "6. `flat` is the flattened output of conv_3 (use [`tf.layers.flatten`](https://www.tensorflow.org/api_docs/python/tf/layers/flatten))\n",
     "7. `dropout_1` is a dropout layer with a dropout rate of 0.5 and should be connected to `flat` (use [`tf.layers.dropout`](https://www.tensorflow.org/api_docs/python/tf/layers/dropout) and be sure to set the `training` argument)\n",
     "8. `fc_1` is a fully-connected layer connected to `dropout_1` with 84 units and ReLU activation (use [`tf.layers.dense`](https://www.tensorflow.org/api_docs/python/tf/layers/dense))\n",
diff --git a/ML-Coursework_Student.ipynb b/ML-Coursework_Student.ipynb
index 5f89b85..d3607f4 100644
--- a/ML-Coursework_Student.ipynb
+++ b/ML-Coursework_Student.ipynb
@@ -1192,7 +1192,7 @@
     "2. `pool_1` is max pooling layer with a 2x2 window with a stride of 2 (use [`tf.layers.max_pooling2d`](https://www.tensorflow.org/api_docs/python/tf/layers/max_pooling2d))\n",
     "3. `conv_2` is 16 filters with a 5x5 kernel size and stride of 1, ReLU activation\n",
     "4. `pool_2` is max pooling layer with a 2x2 window with a stride of 2\n",
-    "5. `conv_3` is 125 filters with a 1x1 kernel size and stride of 1, ReLU activation\n",
+    "5. `conv_3` is 120 filters with a 1x1 kernel size and stride of 1, ReLU activation\n",
     "6. `flat` is the flattened output of conv_3 (use [`tf.layers.flatten`](https://www.tensorflow.org/api_docs/python/tf/layers/flatten))\n",
     "7. `dropout_1` is a dropout layer with a dropout rate of 0.5 and should be connected to `flat` (use [`tf.layers.dropout`](https://www.tensorflow.org/api_docs/python/tf/layers/dropout) and be sure to set the `training` argument)\n",
     "8. `fc_1` is a fully-connected layer connected to `dropout_1` with 84 units and ReLU activation (use [`tf.layers.dense`](https://www.tensorflow.org/api_docs/python/tf/layers/dense))\n",