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In this video, we will review the high-level
features of the Python programming language.

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Python is a powerhouse language.

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It is by far the most popular programming
language for data science.

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According to the 2019 Kaggle Data Science
and Machine Learning Survey, 75% of the over

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10,000 respondents from around the world reported
that they use Python on a regular basis.

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Glassdoor reported that in 2019 more than
75% of data science positions listed included

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Python in their job descriptions.

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When asked which language an aspiring data
scientist should learn first, most data scientists

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say Python.

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You are probably thinking, why on earth is
Python so popular?

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Well, let’s start with the people who use
Python.

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If you already know how to program, then Python
is great for you because it uses clear, readable

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syntax.

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You can do many of the things you are used
to doing in other programming languages but

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with Python you can do it with less code.

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If you want to learn to program, it’s also
a great starter language because of the huge

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global community and wealth of documentation.

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In fact, several different surveys in 2019
found that over 80% of data professionals

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worldwide use Python.

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Python is useful for many situations, including
data science, AI and machine learning, web

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development, and IoT devices like the Raspberry
Pi.

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Large organizations that use Python heavily
include IBM, Wikipedia, Google, Yahoo!, CERN,

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NASA, Facebook, Amazon, Instagram, Spotify,
and Reddit.

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Python is a powerful general-purpose programming
language that can do a lot of things.

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It is widely supported by a global community
and shepherded by the Python Software Foundation.

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1.

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Python is a high-level general-purpose programming
language that can be applied to many different

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classes of problems.

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2.

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It has a large, standard library that provides
tools suited to many different tasks, including

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but not limited to databases, automation,
web scraping, text processing, image processing,

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machine learning, and data analytics.

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3.

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For data science, you can use Python's scientific
computing libraries such as Pandas, NumPy,

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SciPy, and Matplotlib.

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4.

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For artificial intelligence, it has TensorFlow,
PyTorch, Keras, and Scikit-learn.

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5.

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Python can also be used for Natural Language
Processing (NLP) using the Natural Language

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Toolkit (NLTK).

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Another great selling point is the Python
community, which has a well documented history

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of paving the way for diversity and inclusion
efforts in the tech industry as a whole.

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The Python language has a code of conduct
executed by the Python Software Foundation

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that seeks to ensure safety and inclusion
for all, in both online and in person python

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communities.

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There are also communities like PyLadies that
seek to create spaces for people interested

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in Python to learn in safe and inclusive environments.

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PyLadies is an international mentorship group
with a focus on helping more women become

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active participants and leaders in the Python
open source community.