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Columbia University Free Course on Big Data Analytics

Learn how statistics plays a central role in the data science approach from Columbia University USA.

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

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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.

This is the first course in the three-part Data Science and Analytics XSeries.

Brief Details

Length:  5 weeks
Effort:  7 – 10 hours per week
Price:  Free
Institution:  ColumbiaX
Subject:   Data Analysis & Statistics
Level:  Introductory
Languages:  English
Video Transcripts:  English

What you’ll learn

  • Data collection, analysis and inference
  • Relationship between variables
  • Types of association
  • Conditional probability
  • Bayes’ Rule
  • Goals of data visualization
  • Statistical comparisons that underlie data graphics
  • How Bayesian inference is used to combine sources of information
  • Identify situations where Bayesian modeling can be useful

Instructors

  • Eva Ascarza
    Assistant Professor of Marketing at Columbia Business School Columbia University

  • James Curley
    Assistant Professor of Psychology Columbia University

  • Andrew Gelman
    Professor of Statistics and Political Science Columbia University

  • Lauren Hannah
    Assistant Professor in the Department of Statistics Columbia University

  • David Madigan
    Executive Vice President and Dean of Faculty of Arts and Sciences Columbia University

  • Tian Zheng
    Series Creator Columbia University

Course Starts on December 14, 2015

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