diff --git a/docs/source_en/glossary.md b/docs/source_en/glossary.md
index f48ce25ef8cc104dad06c127e94a7ae488630bcd..703328b85a6b336b306db9a1b24dfa45621ce11e 100644
--- a/docs/source_en/glossary.md
+++ b/docs/source_en/glossary.md
@@ -12,8 +12,8 @@
 |  CCE  | Cube-based Computing Engine, which is an operator development tool oriented to hardware architecture programming.  |
 |  CCE-C  |  Cube-based Computing Engine C, which is C code developed by the CCE.  |
 |  CheckPoint  |  MindSpore model training check point, which is used to save model parameters for inference or retraining.  |
-|  CIFAR-10  |  An open-source image data set that contains 60000 32 x 32 color images of 10 categories, with 6000 images of each category. There are 50000 training images and 10000 test images.  |
-|  CIFAR-100  |  An open-source image data set that contains 100 categories. Each category contains 600 images. Each course has 500 training images and 100 test images.  |
+|  CIFAR-10  |  An open-source image dataset that contains 60000 32 x 32 color images of 10 categories, with 6000 images of each category. There are 50000 training images and 10000 test images.  |
+|  CIFAR-100  |  An open-source image dataset that contains 100 categories. Each category has 500 training images and 100 test images.  |
 |  DaVinci  |  DaVinci architecture, Huawei-developed new chip architecture.  |
 |  EulerOS  |  Euler operating system, which is developed by Huawei based on the standard Linux kernel.  |
 |  FC Layer  |  Fully connected layer, which acts as a classifier in the entire convolutional neural network.  |
@@ -40,7 +40,7 @@
 |  MNIST database  |  Modified National Handwriting of Images and Technology database, a large handwritten digit database, which is usually used to train various image processing systems.  |
 |  PyNative Mode  |  MindSpore dynamic graph mode. In this mode, operators in the neural network are delivered and executed one by one, facilitating the compilation and debugging of the neural network model.  |
 |  ResNet-50  |  Residual Neural Network 50, a residual neural network proposed by four Chinese people, including Kaiming He from Microsoft Research Institute.  |
-|  Schema  |  Data set structure definition file, which defines the fields contained in a data set and the field types.  |
+|  Schema  |  Data set structure definition file, which defines the fields contained in a dataset and the field types.  |
 |  Summary  |  An operator that monitors the values of tensors on the network. It is a peripheral operation in the figure and does not affect the data flow.  |
 |  TBE  |  Tensor Boost Engine, an operator development tool that is extended based on the Tensor Virtual Machine (TVM) framework.  |
 |  TFRecord  |  Data format defined by TensorFlow.  |
diff --git a/docs/source_zh_cn/glossary.md b/docs/source_zh_cn/glossary.md
index fd2bce35b3e03aa7276137fafc93441e53a085f0..d5fb6ef6d87796e71696d6b8fc55c54c4ff5f33b 100644
--- a/docs/source_zh_cn/glossary.md
+++ b/docs/source_zh_cn/glossary.md
@@ -13,7 +13,7 @@
 |  CCE-C  |  Cube-based Computing Engine C，使用CCE开发的C代码。  |
 |  CheckPoint  |  MindSpore模型训练检查点，保存模型的参数，可以用于保存模型供推理，或者再训练。  |
 |  CIFAR-10  |  一个开源的图像数据集，包含10个类别的60000个32x32彩色图像，每个类别6000个图像。有50000张训练图像和10000张测试图像。  |
-|  CIFAR-100  |  一个开源的图像数据集，它有100个类别，每个类别包含600张图像。每个课程有500张训练图像和100张测试图像。  |
+|  CIFAR-100  |  一个开源的图像数据集，它有100个类别，每个类别包含500张训练图像和100张测试图像。  |
 |  Davinci  |  达芬奇架构，华为自研的新型芯片架构。  |
 |  EulerOS  |  欧拉操作系统，华为自研的基于Linux标准内核的操作系统。  |
 |  FC Layer  |  Fully Conneted Layer，全连接层。整个卷积神经网络中起到分类器的作用。  |
diff --git a/tutorials/source_en/advanced_use/distributed_training.md b/tutorials/source_en/advanced_use/distributed_training.md
index a3b5225f6208cc579597f691932976c330c9f4a6..0c14495a2720ded6a4d6e0999a634f8907c4fff0 100644
--- a/tutorials/source_en/advanced_use/distributed_training.md
+++ b/tutorials/source_en/advanced_use/distributed_training.md
@@ -107,7 +107,7 @@ if __name__ == "__main__":
 
 ## Loading Datasets
 
-During distributed training, data is imported in data parallel mode. The following uses Cifar10Dataset as an example to describe how to import the CIFAR-10 data set in parallel mode, `data_path` is the path of the dataset.
+During distributed training, data is imported in data parallel mode. The following uses Cifar10Dataset as an example to describe how to import the CIFAR-10 dataset in parallel mode, `data_path` is the path of the dataset.
 Different from a single-node system, the multi-node system needs to transfer `num_shards` and `shard_id` parameters to the dataset API, which correspond to the number of cards and logical sequence number of the NIC, respectively. You are advised to obtain the parameters through the HCCL API.
 
 ```python