Statistical Modeling for Data Science Applications Specialization

Build Your Statistical Skills for Data Science. Master the Statistics Necessary for Data Science

Instructor: Brian Zaharatos

What you'll learn

  •   Correctly analyze and apply tools of regression analysis to model relationship between variables and make predictions given a set of input variables.
  •   Successfully conduct experiments based on best practices in experimental design.
  •   Use advanced statistical modeling techniques, such as generalized linear and additive models, to model wide range of real-world relationships.

    • Skills you'll gain

  •   Statistical Methods
  •   Regression Analysis
  •   Correlation Analysis
  •   R Programming
  •   Predictive Modeling
  •   Statistical Analysis
  •   Statistical Hypothesis Testing
  •   Linear Algebra
  •   Statistical Modeling
  •   Statistical Inference
  •   Probability & Statistics
  •   Data Ethics

    • Specialization - 3 course series

    Learners will master the application and implementation of statistical models through auto-graded and peer reviewed Jupyter Notebook assignments. In these assignments, learners will use real-world data and advanced statistical modeling techniques to answer important scientific and business questions.

    ANOVA and Experimental Design

    Generalized Linear Models and Nonparametric Regression

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