# Academic Events Notebooks

These guides consist of the following three Jupyter notebooks:

* [**Part 1: Data Engineering**](https://github.com/predicthq/phq-data-science-docs/blob/master/academic-events/part_1_data_engineering.ipynb) shows you how to call the Events API to extract the Academic Events data to a DataFrame.
* [**Part 2: Data Exploration**](https://github.com/predicthq/phq-data-science-docs/blob/master/academic-events/part_2_data_exploration.ipynb) is a guide to exploring PredictHQ's Academic Events data for Data Science teams.
* [**Part 3: Feature Engineering**](https://github.com/predicthq/phq-data-science-docs/blob/master/academic-events/part_3_feature_engineering.ipynb) provides examples of how to aggregate and extract features from the data.


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