This 3-day interactive event will lead students through the fundamentals of data analysis and modeling using Python data science libraries. We will focus on the Pandas data frame library as a means of reading, cleaning, and organizing data and explore the Python programming language that underlays its framework. We will explore visualization capabilities, both within Pandas and using the Seaborn statistical visualization library. On the final day, you will learn how to model data using basic linear regression techniques within Pandas and scikit-learn, with an introduction to the sophisticated scikit-learn machine learning framework.
INE ONLINE BOOTCAMP
Data Analysis, Visualization and Predictive Modeling
March 10th-12th, 11:00 AM - 2:00 PM Eastern
ABOUT THE INSTRUCTOR
David Mertz is a data scientist, trainer, and erstwhile startup CTO, who is currently writing the Addison Wesley title Cleaning Data for Successful Data Science: Doing the other 80% of the work. He created the training program for Anaconda, Inc. He was a Director of the Python Software Foundation for six years and remains chair of a few PSF committees. For nine years, David helped with creating the world’s fastest—highly-specialized—supercomputer for performing molecular dynamics.