Organization: Johns Hopkins Bloomberg School of Public Health
Delivery Mode: Online-self study
When Offered: Ongoing
Cost: None
Prerequisites:Following are the prerequisites for this course:
Essential of Probability and Statistical Inference I
Statistical Reasoning in Public Health I
Statistical Methods in Public Health I
Introduction to Probability I
Working knowledge of Calculus
Description: This course introduces the theory and application of modern, computationally based methods for exploring and drawing inferences from data. The topics covered in this course include:
Re-sampling
methods
Non-parametric
regression, Prediction, Dimension reduction and Clustering
Monte
Carlo Simulation and Bootstrap cross-validation
Splines,
Local weighted regression, CART, Random Forests and Neural Networks
Supporting
vector machines, and hierarchical clustering
