Python for Data Science | From Basics to Advanced Python | Be an Expert in Python |FREE CERTIFICATE🥇
Solve Business Problems using Analytics
So, you want to become a DATA SCIENTIST or may be you are already one and want to expand your tool repository. You have landed at the right place. The aim of this channel is to provide a comprehensive learning path to people new to Python for data science. This path provides a comprehensive overview of steps you need to learn to use Python for data science.
Python is an interpreted, high-level, general-purpose programming language. Created by Guido van Rossum and first released in 1991, Python's design philosophy emphasizes code readability with its notable use of significant whitespace.
Table of Contents / Syllabus:
1. Setting up your machine.
2. Basics of Python language.
3. Scientific libraries in Python – NumPy, SciPy, Matplotlib and Pandas.
4. Regular Expressions in Python.
5. Effective Data Visualization.
6. Scikit-learn and Machine Learning.
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The language's core philosophy is summarized in the document The Zen of Python , which includes aphorisms such as:
Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Readability counts.
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