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Course by: Michele Vallisneri

Course Info

Duration: 2h 16m 20s
Skill Level: Intermediate
Released: November 12, 2015
Viewers: 100,458

Learn the most in-demand business, tech and creative skills from industry experts.

Course details

If you’re going to work with big data, you’ll probably be using R or Python. And if you’re using Python, you’ll be definitely using Pandas and NumPy, the third-party packages designed specifically for data analysis. This course provides an opportunity to learn about them. Michele Vallisneri shows how to set up your analysis environment and provides a refresher on the basics of working with data containers in Python. Then he jumps into the big stuff: the power of arrays, indexing, and DataFrames in NumPy and Pandas. He also walks through two sample big-data projects: one using NumPy to analyze weather patterns and the other 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.

Instructor

Michele Vallisneri

Director’s Fellow at JPL (NASA’s Jet Propulsion Laboratory)

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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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