Advanced Linear Models for Data Science 2: Statistical Linear Models

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5

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Course Features

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Duration

6 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Advanced

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Teaching Type

Self Paced

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Video Content

6 hours

Course Description

Welcome to Advanced Linear Models For Data Science Class 2: Statistical Linear Models. This class introduces least squares from both a mathematical and linear algebraic perspective. These are the things you should know before you start the class:

- Basic understanding of multivariate calculus and linear algebra. A basic understanding of statistics, regression models and other statistical concepts. - A basic understanding of proof-based mathematics. Basic knowledge of R programming language. Students will gain a solid foundation in linear algebraic regression modeling after taking this course. This course will enhance the knowledge of applied data scientists about regression models.

Course Overview

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International Faculty

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Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

A basic understanding of linear algebra and multivariate calculus

A basic understanding of statistics and regression models

At least a little familiarity with proof based mathematics

Basic knowledge of the R programming language

Course Instructors

Brian Caffo, PhD

Professor, Biostatistics

Brian Caffo, PhD is a professor in the Department of Biostatistics at the Johns Hopkins University Bloomberg School of Public Health. He graduated from the Department of Statistics at the Universi...

Course Reviews

Average Rating Based on 8 reviews

4.9

88%

13%

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