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Statistical Thinking for Data Science and Analytics

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Statistical Thinking for Data Science and Analytics
Columbia University Online Course Highlights
  • 5 weeks long
  • 7-10 hours per week
  • Learn for FREE, Ugpradable
  • Self-Paced
  • Taught by: Andrew Gelman, David Madigan, Lauren Hannah, James Curley, Eva Ascarza, Tian Zheng
  • View Course Syllabus

Online Course Details:

This statistics and data analysis course will pave the statistical foundation for our discussion on data science.

You will learn how data scientists exercise statistical thinking in designing data collection, derive insights from visualizing data, obtain supporting evidence for data-based decisions and construct models for predicting future trends from data.

What you will learn

  • Data collection, analysis and inference
  • Data classification to identify key traits and customers
  • Conditional Probability-How to judge the probability of an event, based on certain conditions
  • How to use Bayesian modeling and inference for forecasting and studying public opinion
  • Basics of Linear Regression
  • Data Visualization: How to create use data to create compelling graphics

Take This Online Course