diff --git a/6-NLP/5-Hotel-Reviews-2/README.md b/6-NLP/5-Hotel-Reviews-2/README.md
index 678a4053..0b9af8f2 100644
--- a/6-NLP/5-Hotel-Reviews-2/README.md
+++ b/6-NLP/5-Hotel-Reviews-2/README.md
@@ -356,18 +356,17 @@ To review, the steps are:
 
 ### Conclusion
 
-When you started, you had a dataset with columns and data but not all of it could be verified or used. You've explored the data, filtered out what you don't need, converted tags into something useful, calculated your own averages, added some sentiment columns and hopefully, learned some interesting things about processing natural text. The challenge coming up is much easier now that you have wrangled your dataset into something useful!
+When you started, you had a dataset with columns and data but not all of it could be verified or used. You've explored the data, filtered out what you don't need, converted tags into something useful, calculated your own averages, added some sentiment columns and hopefully, learned some interesting things about processing natural text.
 
 ## [Post-lecture quiz](https://jolly-sea-0a877260f.azurestaticapps.net/quiz/40/)
 
 ## Challenge
 
-Todo
+Now that you have your dataset analyzed for sentiment, see if you can use strategies you've learned in this curriculum (clustering, perhaps?) to determine patterns around sentiment. 
 
 ## Review & Self Study
 
-todo
-
+Take [this Learn module](https://docs.microsoft.com/en-us/learn/modules/classify-user-feedback-with-the-text-analytics-api/?WT.mc_id=academic-15963-cxa) to learn more and use different tools to explore sentiment in text.
 ## Assignment 
 
-[todo](assignment.md)
+[Try a different dataset](assignment.md)
diff --git a/6-NLP/5-Hotel-Reviews-2/assignment.md b/6-NLP/5-Hotel-Reviews-2/assignment.md
index d4badb79..5f7e853b 100644
--- a/6-NLP/5-Hotel-Reviews-2/assignment.md
+++ b/6-NLP/5-Hotel-Reviews-2/assignment.md
@@ -1,9 +1,11 @@
-# [Assignment Name]
+# Try a different dataset
 
 ## Instructions
 
+Now that you have learned about using NLTK to assign sentiment to text, try a different dataset. You will probably need to do some data processing around it, so create a notebook and document your thought process. What do you discover?
+
 ## Rubric
 
-| Criteria | Exemplary | Adequate | Needs Improvement |
-| -------- | --------- | -------- | ----------------- |
-|          |           |          |                   |
+| Criteria | Exemplary                                                                                                         | Adequate                                  | Needs Improvement      |
+| -------- | ----------------------------------------------------------------------------------------------------------------- | ----------------------------------------- | ---------------------- |
+|          | A complete notebook and dataset are presented with well-documented cells explaining how the sentiment is assigned | The notebook is missing good explanations | The notebook is flawed |