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Advanced Linear Models for Data Science 2: Statistical Linear Models

Johns Hopkins University via Coursera

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Welcome to the Advanced Linear Models for Data Science Class 2: Statistical Linear Models. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following:

- 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.

After taking this course, students will have a firm foundation in a linear algebraic treatment of regression modeling. This will greatly augment applied data scientists' general understanding of regression models.

Taught by

Brian Caffo
Cost Free Online Course (Audit)
Pace Upcoming
Subject Data Science
Provider Coursera
Language English
Certificates Paid Certificate Available
Calendar 4 weeks long
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Review for Coursera's Advanced Linear Models for Data Science 2: Statistical Linear Models
5.0 Based on 1 reviews

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5.0 10 months ago
by Gaetano Pagani completed this course, spending 4 hours a week on it and found the course difficulty to be medium.
Interesting and really well taught. You must have an advanced learning on matrix algebra and matrix calculus. Some more learning materials would be welcome.
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