Statistics for Data Science with Python

Description

This Statistics for Data Science course is designed to introduce you to the basic principles of statistical methods and procedures used for data analysis. After completing this course you will have practical knowledge of crucial topics in statistics including - data gathering, summarizing data using descriptive statistics, displaying and visualizing data, examining relationships between variables, probability distributions, expected values, hypothesis testing, introduction to ANOVA (analysis of variance), regression and correlation analysis. You will take a hands-on approach to statistical analysis using Python and Jupyter Notebooks – the tools of choice for Data Scientists and Data Analysts.

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Career Relevance by Data Role

The techniques and tools covered in Statistics for Data Science with Python are most similar to the requirements found in Data Scientist job advertisements.


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Fast Facts

Tools
JupyterPythonWatson

Techniques
CorrelationData AnalysisData ScienceData SetsData TypesData VisualizationDistributionsProbabilityProgrammingRegressionStatistical AnalysisVariables

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