diff --git a/docs/source/quick_start.md b/docs/source/quick_start.md
index 902fceaf..ce588945 100644
--- a/docs/source/quick_start.md
+++ b/docs/source/quick_start.md
@@ -19,7 +19,7 @@ pip install -U pykt-toolkit
 ### Prepare a Dataset
 **1、Obtain a Dataset**
 
-Let's start by downloading the dataset from [here](datasets.md). Please make sure you have creat the `data/{dataset_name}` folder
+Let's start by downloading the dataset from [here](datasets.md). Please make sure you have created the `data/{dataset_name}` folder
 <!-- You can find the download link for a dataset from [here](datasets.md). Download the dataset to the `data/{dataset_name}` folder. -->
 
 **2、Data Preprocessing**
@@ -238,4 +238,4 @@ sh start_sweep_0_1.sh
 
 There are only 5 sweeps to be run without any parameter tuning in this stage, with each sweep corresponding to the evaluation of each fold of the training data. Finally, you can export the evaluation results externally or call the wandb API for statistical 5- folds results, and calculate the mean and standard deviation of each metric, i.e., ***mean ± standard deviation***
 
-If you want to add new models or datasets into pyKT, you can follow [Contribute](contribute.md).
\ No newline at end of file
+If you want to add new models or datasets into pyKT, you can follow [Contribute](contribute.md).