In this course, you'll learn how to distinguish between the different types of regression models. You will apply the Method of Least Squares to a dataset by hand and using Python. In addition, you will learn how to employ a linear regression model to identify scenarios. Let's get started!
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Building Regression Models with Linear Algebra
This course is part of Linear Algebra for Data Science Using Python Specialization
Instructors: Dennis Davenport
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There are 4 modules in this course
In module 1, you’ll learn how to define regression and learn about the various types of regression models and how they are used. We will cover the following learning objectives.
What's included
8 videos1 reading3 assignments2 discussion prompts
Let’s recap! In module 1, you learned how to define regression models and use the various types of regression models. In module 2, you’ll gain the knowledge you need to know in order to apply the method of least squares.. You’ll also learn how to apply the method of least squares using Python. We will cover the following learning objectives.
What's included
2 videos3 assignments1 discussion prompt
Let’s recap! In module 2, you learned how to apply the method of least squares. In module 3, you will learn how to understand linear regression models. We will cover the following learning objectives.
What's included
2 videos2 assignments
Welcome to the final module of this course! Over the past 3 modules, you have been introduced to and gained knowledge on the following topics: regression, regression models, applying the method of least squares and, understanding linear regression models. In the final module of the course, you’ll apply what you’ve learned to concrete, real-world examples. You’ll review real-world linear regression models and complete peer reviews. We will cover the following learning objectives.
What's included
2 videos1 peer review
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