Home/Premeable.md

@@ -49,15 +49,17 @@ This document will guid you through the self-learning and the main modules at SA
 
 In this interactive workshop, we will dive into the exciting world of non-invasive sensing and energy monitoring, with a practical application example - a coffee machine! Through hands-on experiences, you will learn how to capture, evaluate, and utilize process data for improvement and efficiency gains.
 
+During our Summerschool we will create, code, train, test and validate an artificial intelligence model to determine the product of a plant based on its energy consumtion data. Our plant will be a simple coffeemaker. :coffee:
+
+A crucial part of a neural network is data. :bulb: Without data, the neural network will not work. Creating this data manually is hard and not efficient. Therefore we will create and label our data for the training our model in an automated manner. For this task some knowledge in microcontroller programming is needed, because we will program an addon, that can be attached to our coffeemachine that will detect wich products are produced, label the data and send it to the network to be processed for the training of our neural network model. 
 
-**TODO: Elaborate Goal:**
 
 ### Languages and Interfaces
 
 The tasks will be realized using two main programming languages:
 
 - C++ to program microcontrollers. 
-- Python for the artificial intelligence part.
+- Python for the artificial intelligence part. :snake:
 
 If you don't have a lot of knowledge about these two programming languages, don't worry. Enough self-learning material will be provided to get you on the needed level. :muscle: