In this six-part series we will explore open data, how to obtain it, how to explore, change, manipulate and visual it. How to deal with Big data, working with hundreds to thousands of files including higher performance methods. Finally a quick dive into open AI methods for extracting, summarizing and even create synthetic data using AI.

2/14 Part 1 - Python Fundamentals
2/21 Part 2 - Obtaining and Working with Data Part 1
2/28 Part 3 - Working with Data 2
3/7 Part 4 - Working with Large Data, Multiple Files and High(er) Performance Processing
3/14 Part 5 - Exploratory Data Visualization
3/21 Part 6 - Open AI for Open Data

Prerequisites: A computer with Python 3.7 or higher and Jupyter Lab/Notebooks installed. Many other packages will be used with a list for each week prior to the session as well as the ability to install them directly from the materials provided. I will show a few things which rely on Python 3.10 and higher, but this is not required. Information on installing Python for new users will be provided prior to the start of the series.