Logistic Regression using R in 10 easy steps!

Logistic Regression using R in 10 easy steps!, available at $19.99, has an average rating of 4.5, with 11 lectures, 2 quizzes, based on 42 reviews, and has 104 subscribers.

You will learn about Learn Logistic Regression using R in 10 steps! Gain hands on experience in building Logistic Regression models using real life case studies Understand the theory & statistics behind Logistic Regression technique Learn how to interpret results from Logistic Regression model This course is ideal for individuals who are Statistics or Business Analytics students or Data Analysts working with financial institutions who would like to build credit/fraud prediction models or Data Analysts working with telecom, retail companies who would like to build customer propensity & churn models or Data Analysts or Data Scientists working with Analytics companies or Any other professionals who would like to build predictive models as part of their job or Aspiring Analytics professionals It is particularly useful for Statistics or Business Analytics students or Data Analysts working with financial institutions who would like to build credit/fraud prediction models or Data Analysts working with telecom, retail companies who would like to build customer propensity & churn models or Data Analysts or Data Scientists working with Analytics companies or Any other professionals who would like to build predictive models as part of their job or Aspiring Analytics professionals.

Enroll now: Logistic Regression using R in 10 easy steps!

Summary

Title: Logistic Regression using R in 10 easy steps!

Price: $19.99

Average Rating: 4.5

Number of Lectures: 11

Number of Quizzes: 2

Number of Published Lectures: 11

Number of Published Quizzes: 1

Number of Curriculum Items: 13

Number of Published Curriculum Objects: 12

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Learn Logistic Regression using R in 10 steps!
Gain hands on experience in building Logistic Regression models using real life case studies
Understand the theory & statistics behind Logistic Regression technique
Learn how to interpret results from Logistic Regression model

Who Should Attend

Statistics or Business Analytics students
Data Analysts working with financial institutions who would like to build credit/fraud prediction models
Data Analysts working with telecom, retail companies who would like to build customer propensity & churn models
Data Analysts or Data Scientists working with Analytics companies
Any other professionals who would like to build predictive models as part of their job
Aspiring Analytics professionals

Target Audiences

Statistics or Business Analytics students
Data Analysts working with financial institutions who would like to build credit/fraud prediction models
Data Analysts working with telecom, retail companies who would like to build customer propensity & churn models
Data Analysts or Data Scientists working with Analytics companies
Any other professionals who would like to build predictive models as part of their job
Aspiring Analytics professionals

Why Logistic Regression?

If you would like to become a data analyst/data scientist or take up a project on data analytics, then knowledge on predictive analytics is a key milestone as a large fraction of data analytics projects will be on predictive analytics.

Logistic Regression is one of the most commonly used predictive analytics techniques across domains like finance, healthcare, marketing, retail and telecom. It can help to predict the probability of occurrence of an event i.e. Logistic Regression can answer the questions like –

What is the probability that the customer will buy the product?
What is the probability that the debtor will pay back the loan?
What is the probability that your favorite team is going to win the match?
What is the probability that the employee will churn?

and so on…

What does this course cover?

This course covers logistic regression end-to-end using R in 10 steps, with a real life case study!

You will learn –

Data preparation
Model building
Model validation
Model assessment
Model implementation

What are the advantages of taking this course?

The course is completely done in R, an open source statistical language that is very popular among the data scientists today.
You will get the complete R code, dataset, data dictionary for the case study along with the lectures, as a part of this course.
This course will make equip you to take up a new Logistic Regression assignment on your own!

Who should enroll for this course?

Aspiring data analysts, students or any one keen on learning Logistic Regression from the basics

What are the prerequisites for this course?

Basic R

Course Curriculum

Chapter 1: Logistic Regression – Overview, Model Building, Assessment & Implementation

Lecture 1: 1. Introduction to Predictive Modeling

Lecture 2: 2. Logistic Regression Overview

Lecture 3: 3. Case Study

Lecture 4: 4. Data Partitioning

Lecture 5: 5. Univariate Analysis

Lecture 6: 6. Bivariate Analysis

Lecture 7: 7. Multicollinearity Analysis

Lecture 8: 8. Model Building

Lecture 9: 9. Model Validation

Lecture 10: 10. Model Performance Assessment

Lecture 11: 11. Scorecard

Instructors

Aze Analytics
Learn Data Analytics!

Rating Distribution

1 stars: 3 votes
2 stars: 1 votes
3 stars: 9 votes
4 stars: 8 votes
5 stars: 21 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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