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Statistics for Data Science with Python

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.

Created by IBM


What you’ll learn

In this learning opportunity you can acquire the compentencies required by employers these days. The most in demand technique in the educational resource that is often requested by organizations is Data Analysis. The most in demand tool is Python. You will also learn about Communication Skills, a trait commonly mentioned in job advertisements.

Who will benefit?

Comparing material from this educational resource with nearly 10,000 data-related job descriptions, we find that those in or pursuing Data Scientist roles have the most to gain.