Duration: 1h57m | Video: .MP4 1280x720, 30 fps(r) | Audio: AAC, 48000Hz, 2ch | Size: 0.98 GB
Genre: eLearning | Language: English
Statistics introduction applied to data science to perform a good exploratory data analysis.
What you'll learn
Descriptive Statistics.
Pivot Table.
HeatMap.
Histograms.
Box-Description.
Regression and Correlation.
Anova.
Chi-Square.
Introduction to Time Series.
And much more.
Requirements
Basic training in mathematics and use of a web browser.
Knowledge of the Python language is desirable but not essential.
Description
In this course we will learn the basic statistical techniques to perform an Exploratory Data Analysis in a professional way. It combines both theory and practice. We use Python Jupyter Notebooks as a technology tool of support. Knowledge of the Python language is desirable, but not essential, since during the course the necessary knowledge to carry out the labs and exercises will be provided.
Who this course is for:
Students and professionals who wish to acquire or improve their skills in data analysis through statistical techniques.
Python developers who want to improve their skills using statistical techniques.
Data analysts.
Beginning python developers interested in data science.
Homepage
https://www.udemy.com/course/statistics-introduction-applied-to-data-science/Buy Premium From My Links To Get Resumable Support,Max Speed & Support Me
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