Advanced Linear Models for Data Science 2: Statistical Linear Models
About this Course
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.Created by: Johns Hopkins University
Related Online Courses
Analyse the role of data, volume, quality, and timeliness, in decision making and critically evaluate, with particular reference to digital data, traditional leadership models In this course, you... more
Discover the principles of solid scientific methods in the behavioral and social sciences. Join us and learn to separate sloppy science from solid research! This course will cover the fundamental... more
This Specialization is intended for beginners seeking to enter the artificial intelligence world. Through five courses, you will cover artificial intelligence technical groundings (including... more
Use statistical learning techniques like linear regression and classification to solve common machine learning problems. Complete short coding assignments in Python.Created by: University of... more
Through hands-on projects and expert-led instruction, you\'ll learn the entire UX design process, from conducting user research and creating wireframes to designing high-fidelity mockups and... more
Powered by
