diff --git a/doc/fluid/beginners_guide/index.rst b/doc/fluid/beginners_guide/index.rst
index b15106692b45e8cd476763add88c0b71c8b96871..d90c8dd61318b0ea5ddd14f3983067c66e073068 100644
--- a/doc/fluid/beginners_guide/index.rst
+++ b/doc/fluid/beginners_guide/index.rst
@@ -13,3 +13,4 @@
     quick_start/index.rst
     basics/index.rst
     basics/learning_materials.md
+    programming_guide/programming_guide.md
diff --git a/doc/fluid/beginners_guide/programming_guide.md b/doc/fluid/beginners_guide/programming_guide/programming_guide.md
similarity index 98%
rename from doc/fluid/beginners_guide/programming_guide.md
rename to doc/fluid/beginners_guide/programming_guide/programming_guide.md
index a239a271ad1fb17fb2f149fe0ccf016766f0dc89..8a328beac0cee3ad0f1fe4117a6f67681eb2587a 100644
--- a/doc/fluid/beginners_guide/programming_guide.md
+++ b/doc/fluid/beginners_guide/programming_guide/programming_guide.md
@@ -15,9 +15,9 @@
 
 Fluid和其他主流框架一样，使用Tensor数据结构来承载数据。
 
-在神经网络中传递的数据都是Tensor,Tensor可以简单理解成一个多维数组，一般而言可以有任意多的维度。
+在神经网络中传递的数据都是Tensor,Tensor可以简单理解成一个多维数组，一般而言可以有任意多的维度。不同的Tensor可以具有自己的数据类型和形状，同一Tensor中每个元素的数据类型是一样的，Tensor的形状就是Tensor的维度。
 
-不同的Tensor可以具有自己的数据类型和形状，同一Tensor中每个元素的数据类型是一样的，Tensor的形状就是Tensor的维度。下面的图直观地表示1～6维的Tensor： 
+下图直观地表示1～6维的Tensor： 
 <p align="center">
 <img src="https://raw.githubusercontent.com/PaddlePaddle/FluidDoc/develop/doc/fluid/beginners_guide/image/tensor.jpg" width="400">
 </p>
diff --git a/doc/fluid/user_guides/fluid_design_idea.md b/doc/fluid/user_guides/design_idea/fluid_design_idea.md
similarity index 99%
rename from doc/fluid/user_guides/fluid_design_idea.md
rename to doc/fluid/user_guides/design_idea/fluid_design_idea.md
index c166d8193330d7498bfdbc65d895ed9a5cb4bf79..f5f5d8cd67bfe9d891151faffd4fe83410c69889 100644
--- a/doc/fluid/user_guides/fluid_design_idea.md
+++ b/doc/fluid/user_guides/design_idea/fluid_design_idea.md
@@ -324,7 +324,7 @@ dims表示数据的维度，这里表示 x 的维度为[-1,1]，其中-1是batch
 
 **创建Executor**
 
-Fluid使用Executor来执行网络训练，executor运行细节请参考[Executor设计思想](#Executor设计思想)的介绍。作为使用者，实际并不需要了解内部机制。
+Fluid使用Executor来执行网络训练，Executor运行细节请参考[Executor设计思想](#Executor设计思想)的介绍。作为使用者，实际并不需要了解内部机制。
 
 创建Executor只需调用 fluid.Executor(place) 即可，在此之前请您依据训练场所定义place变量：
 ```python
diff --git a/doc/fluid/user_guides/image/executor_design.png b/doc/fluid/user_guides/design_idea/image/executor_design.png
similarity index 100%
rename from doc/fluid/user_guides/image/executor_design.png
rename to doc/fluid/user_guides/design_idea/image/executor_design.png
diff --git a/doc/fluid/user_guides/image/fluid_process.png b/doc/fluid/user_guides/design_idea/image/fluid_process.png
similarity index 100%
rename from doc/fluid/user_guides/image/fluid_process.png
rename to doc/fluid/user_guides/design_idea/image/fluid_process.png
diff --git a/doc/fluid/user_guides/index.rst b/doc/fluid/user_guides/index.rst
index 8dc5fa2389efea77e55553def3c1bc78aba13c29..b01db04979d29815c89cd215bab04ae162f1da56 100644
--- a/doc/fluid/user_guides/index.rst
+++ b/doc/fluid/user_guides/index.rst
@@ -17,3 +17,4 @@
     howto/evaluation/index
     howto/inference/index
     models/index.md
+    design_idea/fluid_design_idea.md