diff --git a/intro-neural-networks/student-admissions/StudentAdmissions.ipynb b/intro-neural-networks/student-admissions/StudentAdmissions.ipynb
index 37b296a7d4..73ba32d197 100644
--- a/intro-neural-networks/student-admissions/StudentAdmissions.ipynb
+++ b/intro-neural-networks/student-admissions/StudentAdmissions.ipynb
@@ -188,7 +188,7 @@
    "metadata": {},
    "source": [
     "## Splitting the data into features and targets (labels)\n",
-    "Now, as a final step before the training, we'll split the data into features (X) and targets (y)."
+    "Now, as a final step before the training, we'll split the data into features (X) and targets (y). We must also convert the values in the one hot encoded ranks from a boolean (true or false) to a float (1 or 0)."
    ]
   },
   {
@@ -201,6 +201,7 @@
     "targets = train_data['admit']\n",
     "features_test = test_data.drop('admit', axis=1)\n",
     "targets_test = test_data['admit']\n",
+    "features = features.astype(float)\n",
     "\n",
     "print(features[:10])\n",
     "print(targets[:10])"
@@ -324,7 +325,7 @@
    "outputs": [],
    "source": [
     "# Calculate accuracy on test data\n",
-    "test_out = sigmoid(np.dot(features_test, weights))\n",
+    "test_out = sigmoid(np.dot(features_test.astype(float), weights))\n",
     "predictions = test_out > 0.5\n",
     "accuracy = np.mean(predictions == targets_test)\n",
     "print(\"Prediction accuracy: {:.3f}\".format(accuracy))"