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Data science is transforming the way that government and industry leaders look at both specific problems and the world at large. Curious about how data analysis actually works in practice? In this course, instructor Michele Vallisneri shows you how, explaining what it takes to get started with data science using Python.
Michele demonstrates how to set up your analysis environment and provides a refresher on the basics of working with data structures in Python. Then, he jumps into the big stuff: the power of arrays, indexing, and tables in NumPy and pandas—two popular third-party packages designed specifically for data analysis. He also walks through two sample big-data projects: using NumPy to identify and visualize weather patterns and using pandas to analyze the popularity of baby names over the last century. Challenges issued along the way help you practice what you’ve learned.
Note: This version of the course was updated to reflect recent changes in Python 3, NumPy, and pandas.
Michele Vallisneri is a theoretical astrophysicist at NASA Jet Propulsion Laboratory.
He obtained his PhD in physics at the California Institute of Technology in 2002. His research spans the detection and interpretation of gravitational waves with LIGO, in space, and with pulsar timing. He is an expert in data analysis, Bayesian inference, and computational physics, and he believes that elegant, transparent programming can illuminate the hardest problems. He is a Fellow of the American Physical Society, and he was awarded the NASA Exceptional Scientific Achievement Medal.
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