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Cursos disponibles
Aim of Course:
This course covers how to read, understand, manipulate, and use data. There is no prerequisite knowledge for this course, but it does require access to Excel.
- Teacher: Alex Cunningham
Aim of Course:
This course shell holds an assessment test for Church & Dwight Data Analytics Training program.
Aim of Course:
This course will explain the theory of generalized linear models (GLM), outline the algorithms used for GLM estimation, and explain how to determine which algorithm to use for a given data analysis.
Aim of Course:
This course will teach you how to build and monitor a machine learning pipeline, given a predictive model that has been provided by a data science team.
- Teacher: Andrew Stewart
- Teacher: Ramzi Ziade
Aim of Course:
This course will explain the basic theory of linear and non-linear mixed effects models, including hierarchical linear models. It will outline the algorithms used for estimation, primarily for models involving normally distributed errors, and will provide examples of data analysis. The course aims at providing a basic understanding and knowledge of the mixed effect models that will allow you to use them in practice.
- Teacher: James Hardin
Aim of Course:
This course covers the analysis of data gathered in surveys.
- Teacher: Anthony Babinec
Aim of Course:
This course covers the basic theory and application of the bootstrap family of procedures, with the emphasis on applications.
- Teacher: Robert LaBudde
Aim of Course:
This course describes the various methods used for modeling and evaluating survival data, also called time-to-event data.
- Teacher: Anthony Babinec
Aim of Course:
After taking this course, you will be able to install and run rjags, a program for Bayesian analysis within R. Using R and rjags, you will learn how to specify and run Bayesian modeling procedures using regression models for continuous, count and categorical data.
- Teacher: Peter Congdon
Aim of Course:
This course covers how to apply linear programming to complex systems to make better decisions – decisions that increase revenue, decrease costs, or improve efficiency of operations.
- Teacher: Ken Strasma