[Lesson 19] Add assignement

5-Data-Science-In-Cloud/19-tbd/assignment.md

@@ -1,8 +1,11 @@
-# Title
+# Data Science in the Cloud: The "Azure ML SDK" way 
 
 ## Instructions
 
+We saw how to use the Azure ML platform to train, deploy and consume a model with the Azure ML SDK. Now look around for some data that you could use to train an other model, deploy it and consume it. You can look for datasets on [Kaggle](https://kaggle.com) and [Azure Open Datasets](https://azure.microsoft.com/en-us/services/open-datasets/catalog/?WT.mc_id=academic-15963-cxa).
+
 ## Rubric
 
-Exemplary | Adequate | Needs Improvement
+| Exemplary | Adequate | Needs Improvement |
---- | --- | -- |
+|-----------|----------|-------------------|
+|When doing the AutoML Configuration, you went through the SDK documentation to see what parameters you could use. You ran a training on a dataset through AutoML using Azure ML SDK, and you checked the model explanations. You deployed the best model and you were able to consume it through the Azure ML SDK. | You ran a training on a dataset through AutoML using Azure ML SDK, and you checked the model explanations. You deployed the best model and you were able to consume it through the Azure ML SDK. | You ran a training on a dataset through AutoML using Azure ML SDK. You deployed the best model and you were able to consume it through the Azure ML SDK. |