courses for review by invited guests to our Learning Management System

Aim of Course:

This course will introduce you to the basic concepts in predictive analytics, also called predictive modeling, the most prevalent form of data mining.

Aim of Course:

This course covers clinical trial designs including randomized controlled trials, ROC curves, CI and tests for relative risk and odds ratio, and an introduction to survival analysis.

Aim of Course:

To provide an easy introduction to statistical inference for a single variable.

Aim of Course:

This course continues the work of Predictive Analytics 1, and introduces you to additional techniques in predictive analytics, also called predictive modeling, the most prevalent form of data mining.

Aim of Course:

This course will introduce you to the basic concepts in predictive analytics, also called predictive modeling, the most prevalent form of data mining.

Aim of Course:

This course, the second in a three-course sequence, provides an easy introduction to inference and association through a series of practical applications, based on the resampling/simulation approach.

Aim of Course:

In this online course, you will learn how to examine data with the goal of detecting anomalies or abnormal instances. This task is critical in a wide range of applications ranging from fraud detection to surveillance.