# Week 4 - Versioning with Git and Data Preparation (Part 2)

### This week we will...

cover the following topics:

* Versioning with Git in a Team
* Important Issues to Consider for Feature Engineering
* Introduction into Analyzing Time Series Data

### Learning Resources

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### Until next week you should...

* [x] meet with your team to discuss potential additional variables to be created for sales prediction (including whether there are any additional data sources you can use).<br>
* [x] analyze the time series data for the 6 product groups using moving averages, percent change, or segmentation (see learning material).<br>
* [x] update the "Data Import and Preparation" directory in your team repository to include:
  * Additional downloaded or self-created data (e.g., holiday lists)
  * Code to merge all data into one dataset
  * Code to create new variables or prepare existing variables for prediction<br>
* [x] Get A [Kaggle](https://www.kaggle.com/) account and review the course competition under:\
  <https://www.kaggle.com/t/d832497c95d744de915ad9eb80ad9ed6><br>
* [x] watch the following videos from the DeepLearning.AI course on Python for Data Analytics to get an idea about how to analyze time series data:
  * [DateTimes](https://learn.deeplearning.ai/specializations/data-analytics/lesson/yt06e/datetimes) (5 minutes)
  * [Using DateTimes as Indices](https://learn.deeplearning.ai/specializations/data-analytics/lesson/xtibp/using-datetimes-as-indices) (3 minutes)
  * [Moving Averages](https://learn.deeplearning.ai/specializations/data-analytics/lesson/n5vs5/moving-average) (5 minutes)
  * [Percent Change](https://learn.deeplearning.ai/specializations/data-analytics/lesson/icu5f/percent-change) (4 minutes)
  * [Segmentation](https://learn.deeplearning.ai/specializations/data-analytics/lesson/n5s9q/segmentation) (5 minutes)

*(You need to create a free account with DeeplLearning.AI.)*<br>