Readme file updates.

emp-churn-step-by-step/README.md

@@ -27,14 +27,55 @@ pip install h2o-wave
 Once the virtual environment is setup and active, run:
 
 ```sh
-wave run app.py
+# To run first example
+wave run app1.py
+
+# To run thelast example App
+wave run app13.py
 ```
 
 Which will start a Wave app at <http://localhost:10101>.
 
-## Interactive examples
 
-If you prefer learning by doing, you can run `wave fetch` command that will download all the existing small Python examples that show Wave in action. The best part is that all these examples are interactive, meaning you can edit their code directly within the browser and observe the changes.
+
+## Application topics
+
+This is is the set of applications (from app1 to app13) which demonstrate how to develop Wave application step by step. Each step adds additional functionality.
+
+List of training Apps:
+
+- `app1` through `app8` - step by step development of Employee Churn dashboard
+- `app9` - adding debugging and logging
+- `app10 `- refactoring app9 to refresh content only when there is a change due to user interaction. In the previous steps we have re-drawn cards every time there was a change
+- `app11` - This app is the same as `app10`, but it pulls data from Delta Lake storage.
+- `app12` - This app adds pagination logic to `app10`.
+- `app13` - This app adds tabs and tab switching to `app12`. Cards are recreated only when tab switching is detected.
+
+
+
+## Interactive Wave University examples
+
+If you don't feel like going through the docs because you are more of a hands-on person, you can try our Wave University app.
+
+Within your activated virtual environment, run:
+
+```sh
+wave learn
+```
+
+
+
+The command requires `h2o_wave_university` to be installed. To do that, run:
+
+```sh
+pip install h2o_wave_university
+```
+
+
+
+Wave University documentation link: https://wave.h2o.ai/docs/getting-started#interactive-learning 
+
+
 
 ## Learn More
 

emp-churn-step-by-step/src/app2.py

@@ -44,7 +44,6 @@ async def init(q: Q) -> None:
         title='Employee Churn Prediction',
         subtitle="Predict which employees are at risk and identify relevant factors."
     )
-    import os
     q.page['footer'] = ui.footer_card(
         box='footer',
         caption='Made with 💛 using [H2O Wave](https://wave.h2o.ai).'