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Data Science. Logistic Regression

About the course

In this course, you will learn what is a logistic regression model, what it is used for, and how to fit a model to real data using RStudio.

If you do not have RStudio on your computer yet, go ahead and download it for free from the RStudio website. You will also need to download and instal R from the CRAN website.

The course is composed by two lessons:

  1. A Theory Lesson, where we will cover some fundamental theory on logistic regression and complete a detailed tutorial on logistic regression in RStudio. The theoretical concepts covered in Module 1.1 are not necessary to complete the exercises, but they will help you a great deal in understanding why things work the way they do. Module 1.2 will give you all the necessary information to complete the exercises included in the next lesson.
  2. A Practice Lesson, with many exercises to test your newly acquired skills! Every module of the Practice Lesson can be completed independently, so feel free to skip around and focus on what is more important or challenging to you. At the beginning of each exercise, we will tell if data and/or libraries need to be imported to complete it.

Instructors

  1. Giulia Toti is currently working as a postdoc for the Addiction department at King's College London. She was awarded with the PhD in Computer Science at the University of Houston in 2016. Previously, she completed her MS in Biomedical Engineering at the Polytechnic of Turin. Her work focuses on development and application of machine learning techniques to the medical field, with particular attention to risk analysis, prognostic models, and mining of large databases of electronic health records.

Reviews

Vasilii Feofanov July 29, 2017 link
Rated:  5
It is a good course that can be considered as a practical guide for logistic regression using R. The course gives a recommendation how to make a model selection as well as how to interpret correctly coefficients of a model. For better understanding, two real datasets are used for exercises. The course does not provide to you deep theory or mathematical substantiation. So, I consider this course as a nice supplement to such materials as https://stepik.org/524 (in Russian) or any appropriate textbook (e.g. "Hastie et al. - The Elements of Statistical Learning").
5 All reviews

In this course, you will learn what is a logistic regression model, what it is used for, and how to fit a model to real data using RStudio.

Expected time to complete:
1 hour
Language:
English
Certificate:
Not issuing

About the course

In this course, you will learn what is a logistic regression model, what it is used for, and how to fit a model to real data using RStudio.

If you do not have RStudio on your computer yet, go ahead and download it for free from the RStudio website. You will also need to download and instal R from the CRAN website.

The course is composed by two lessons:

  1. A Theory Lesson, where we will cover some fundamental theory on logistic regression and complete a detailed tutorial on logistic regression in RStudio. The theoretical concepts covered in Module 1.1 are not necessary to complete the exercises, but they will help you a great deal in understanding why things work the way they do. Module 1.2 will give you all the necessary information to complete the exercises included in the next lesson.
  2. A Practice Lesson, with many exercises to test your newly acquired skills! Every module of the Practice Lesson can be completed independently, so feel free to skip around and focus on what is more important or challenging to you. At the beginning of each exercise, we will tell if data and/or libraries need to be imported to complete it.

Requirements

We recommend this course to students who have some familiarity with the vary basic principles of statistics and probability (means, proportions...). We also encourage students who do not have any experience with RStudio to get acquainted with the software before tackling the exercises of this course. In particular, students should know how to install and import new libraries in order to have access to all the functions used in the exercises.

This course is entirely free. All content is available now.