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As an aspiring data scientist, you appreciate why organizations
rely on data for important decisions--whether it's for companies
designing websites, cities deciding how to improve services, or
scientists discovering how to stop the spread of disease. And you
want the skills required to distill a messy pile of data into
actionable insights. We call this the data science lifecycle: the
process of collecting, wrangling, analyzing, and drawing
conclusions from data. Learning Data Science is the first book to
cover foundational skills in both programming and statistics that
encompass this entire lifecycle. It's aimed at those who wish to
become data scientists or who already work with data scientists,
and at data analysts who wish to cross the "technical/nontechnical"
divide. If you have a basic knowledge of Python programming, you'll
learn how to work with data using industry-standard tools like
pandas. Refine a question of interest to one that can be studied
with data Pursue data collection that may involve text processing,
web scraping, etc. Glean valuable insights about data through data
cleaning, exploration, and visualization Learn how to use modeling
to describe the data Generalize findings beyond the data
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