diff --git a/01_intro.ipynb b/01_intro.ipynb
index 7ba1e76..4014d9b 100644
--- a/01_intro.ipynb
+++ b/01_intro.ipynb
@@ -2721,7 +2721,7 @@
     "\n",
     "It's instructive to look at a few example cases. Many of these examples come from predictive modeling competitions on the [Kaggle](https://www.kaggle.com/) platform, which is a good representation of problems and methods you might see in practice.\n",
     "\n",
-    "One case might be if you are looking at time series data. For a time series, choosing a random subset of the data will be both too easy (you can look at the data both before and after the dates your are trying to predict) and not representative of most business use cases (where you are using historical data to build a model for use in the future). If your data includes the date and you are building a model to use in the future, you will want to choose a continuous section with the latest dates as your validation set (for instance, the last two weeks or last month of available data).\n",
+    "One case might be if you are looking at time series data. For a time series, choosing a random subset of the data will be both too easy (you can look at the data both before and after the dates you are trying to predict) and not representative of most business use cases (where you are using historical data to build a model for use in the future). If your data includes the date and you are building a model to use in the future, you will want to choose a continuous section with the latest dates as your validation set (for instance, the last two weeks or last month of available data).\n",
     "\n",
     "Suppose you want to split the time series data in <<timeseries1>> into training and validation sets."
    ]