diff --git a/4-Data-Science-Lifecycle/14-Introduction/README.md b/4-Data-Science-Lifecycle/14-Introduction/README.md
index e248c16f..20e7c12d 100644
--- a/4-Data-Science-Lifecycle/14-Introduction/README.md
+++ b/4-Data-Science-Lifecycle/14-Introduction/README.md
@@ -4,8 +4,6 @@
 |:---:|
 | Introduction to the Data Science Lifecycle - _Sketchnote by [@nitya](https://twitter.com/nitya)_ |
 
-## Pre-Lecture Quiz
-
 ## [Pre-Lecture Quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/26)
 
 At this point you've probably come to the realization that data science is a process. This process can be broken down into 5 stages:
@@ -93,8 +91,7 @@ Explore the [Team Data Science Process lifecycle](https://docs.microsoft.com/en-
 |![](..\images\tdsp-lifecycle2.png)> Photo by [Microsoft](https://docs.microsoft.com/en-us/azure/architecture/data-science-process/lifecycle)| ![](..\images\CRISP-DM.png)> Photo by [Data Science Process Alliance](https://www.datascience-pm.com/crisp-dm-2/)
 
 
-## Post-Lecture Quiz
-[Post-lecture quiz]()
+## [Post-Lecture Quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/27)
 
 ## Review & Self Study
 
@@ -105,4 +102,4 @@ Applying the Data Science Lifecycle involves multiple roles and tasks, where som
 
 ## Assignment
 
-[Exploring and Assessing a Dataset](assignment.md)
+[Assessing a Dataset](assignment.md)
diff --git a/4-Data-Science-Lifecycle/14-Introduction/assignment.md b/4-Data-Science-Lifecycle/14-Introduction/assignment.md
index 44f8436c..36b01d5d 100644
--- a/4-Data-Science-Lifecycle/14-Introduction/assignment.md
+++ b/4-Data-Science-Lifecycle/14-Introduction/assignment.md
@@ -1,18 +1,20 @@
-# Exploring and Assessing a Dataset
+# Assessing a Dataset
 
 A client has approached your team for help in investigating a taxi customer's seasonal spending habits in New York City. 
 
 They want to know: **Do yellow taxi passengers in New York City tip drivers more in the winter or summer?**
 
-Your team is in the [Capturing](Readme.md#Capturing) stage of the Data Science Lifecycle and you are in charge of exploring the dataset. You have been provided a notebook and data from Azure Open Datasets to explore and assess if the data can answer the client's question. You have decided to select a small sample of 1 summer month and 1 winter month in the year 2019.
+Your team is in the [Capturing](Readme.md#Capturing) stage of the Data Science Lifecycle and you are in charge of handling the the dataset. You have been provided a notebook and [data](../../data/taxi.csv) to explore.
 
-## Instructions
+In this directory is a [notebook](notebook.ipynb) that uses Python to load yellow taxi trip data from the [NYC Taxi & Limousine Commission](https://docs.microsoft.com/en-us/azure/open-datasets/dataset-taxi-yellow?tabs=azureml-opendatasets).
+You can also open the taxi data file in text editor or spreadsheet software like Excel.
 
-In this directory is a [notebook](notebook.ipynb) that uses Python to load yellow taxi trip data from the [NYC Taxi & Limousine Commission](https://docs.microsoft.com/en-us/azure/open-datasets/dataset-taxi-yellow?tabs=azureml-opendatasets) for the months of January and July 2019. These datasets have been joined together in a Pandas dataframe.
+## Instructions
 
-Your task is to identify the columns that are the most likely required to answer this question, then reorganize the joined dataset so that these columns are displayed first.
+- Assess whether or not the data in this dataset can help answer the question.
+- Write 3 questions that you would ask the client for more clarification and better understanding of the problem. 
 
-Finally, write 3 questions that you would ask the client for more clarification and better understanding of the problem.
+Refer to the [dataset's dictionary](https://www1.nyc.gov/assets/tlc/downloads/pdf/data_dictionary_trip_records_yellow.pdf) for more information about the
 
 ## Rubric
 
diff --git a/4-Data-Science-Lifecycle/14-Introduction/notebook.ipynb b/4-Data-Science-Lifecycle/14-Introduction/notebook.ipynb
index cce66031..e4041090 100644
--- a/4-Data-Science-Lifecycle/14-Introduction/notebook.ipynb
+++ b/4-Data-Science-Lifecycle/14-Introduction/notebook.ipynb
@@ -1,20 +1,11 @@
 {
   "cells": [
-    {
-      "cell_type": "markdown",
-      "source": [
-        "Copyright (c) Microsoft Corporation. All rights reserved.\r\n",
-        "\r\n",
-        "Licensed under the MIT License."
-      ],
-      "metadata": {}
-    },
     {
       "cell_type": "markdown",
       "source": [
         "# Exploring NYC Taxi data in Winter and Summer\r\n",
         "\r\n",
-        "Refer to the [Data dictionary](https://www1.nyc.gov/assets/tlc/downloads/pdf/data_dictionary_trip_records_yellow.pdf) to explore the columns that have been provided.\r\n"
+        "Refer to the [Data dictionary](https://www1.nyc.gov/assets/tlc/downloads/pdf/data_dictionary_trip_records_yellow.pdf) to learn more about the columns that have been provided.\r\n"
       ],
       "metadata": {}
     },
@@ -37,12 +28,7 @@
         "import glob\r\n",
         "\r\n",
         "path = '../../data/taxi.csv'\r\n",
-        "# july_taxi = pd.read_csv(path.format('07'))\r\n",
-        "# january_taxi = pd.read_csv(path.format('01'))\r\n",
-        "\r\n",
-        "# df = pd.concat([july_taxi.sample(100), january_taxi.sample(100)])\r\n",
         "df = pd.read_csv(path)\r\n",
-        "# df.describe()\r\n",
         "print(df)\r\n"
       ],
       "outputs": [