Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
Linear Regression and Modeling certification is a 4 weeks course that only takes 10 hours in total from a candidate. This course is a collaborative effort between Duke University, and Coursera. The main aim that both these platforms have is to introduce both linear regression models- simple and multiple regression. With these models, one can judge a relationship between the different variable data points in a data set.
Linear Regression and Modeling training will help with the basics of linear regression that is used with data examples for learning, examining, and ultimately utilizing these, to sum up, the relationship between variables that are multiple. An example of such a case is that the training will let the students find out the relationships between how attractive a professor is, and on what parameters does he or she evaluate students. This relationship is usually examined by using statistical software like R, and RStudio which is free of cost.
The Highlights
- 4 weeks programme
- 100% online course
- 10 hours of classes
- Learning by self
- Beginner course level
- 10 subtitles available
- Certificate by Coursera
Programme Offerings
- Online Course
- Shareable Certificate
- Flexible Deadlines
- Graded Assignments
- English Course
- 10 Subtitles Available
- Lectures
- videos
- Readings
- Practice Exercises.
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Coursera |
Linear Regression and Modeling Fee Structure
Course name | Fee in INR |
| Audit mode | Free |
Linear Regression and Modeling (1 month) | Rs. 4,115 |
| Linear Regression and Modeling (3 months) | Rs. 8,230 |
| Linear Regression and Modeling (6 months) | Rs. 12,345 |
Eligibility Criteria
Educational Qualification
Knowing Portuguese (European), Italian, French, Korean, German, Arabic, Vietnamese, Spanish, Russian, and English, will help since the course comes with these subtitles.
Certification Qualifying Details
For the Linear Regression and Modeling certification by Coursera, participants will always have to complete everything that is stated in the curriculum on the website.
What you will learn
With this Linear Regression and Modeling certification syllabus, the candidates will be learning the very basic, and fundamental concepts with examples regarding linear regression, statistics, and R programming.
Admission Details
The Linear Regression and Modeling admission process is as follows:
Step 1: Visit the official website: https://www.coursera.org/learn/linear-regression-model
Step 2: Then, find the ‘Join for free’ button on the course website and click it.
Step 3: Then on the webpage, give proper details like valid email id, and names, to set up their account on Coursera.
Step 4: As soon as an account gets made, candidates can log in to pay the fee, and seek admission.
Application Details
The regular application form is not required on Coursera. The only information that students need to provide is their personal details like email and name to get done with a new Coursera account.
The Syllabus
Videos
Introduction to Statistics with R
Readings
- About Statistics with R Specialization
- More about Linear Regression and Modeling
Videos
- Introduction
- Correlation
- Residuals
- Least Squares Line
- Prediction and Extrapolation
- Conditions for Linear Regression
- R Squared
- Regression with Categorical Explanatory Variables
Readings
- Lesson Learning Objectives
- Lesson Learning Objectives
- Week 1 Suggested Readings and Practice
Assignments
- Week 1 Practice Quiz
- Week 1 Quiz
Videos
- Outliers in Regression
- Inference for Linear Regression
- Variability Partitioning
Readings
- Lesson Learning Objectives
- Week 2 Suggested Readings and Exercises
- About Lab Choices
- Week 1 & 2 Lab Instructions (RStudio)
- Week 1 & 2 Lab Instructions (RStudio Cloud)
Assignments
- Week 2 Practice Quiz
- Week 2 Quiz
- Week 1 & 2 Lab
Videos
- Introduction
- Multiple Predictors
- Adjusted R Squared
- Collinearity and Parsimony
- Inference for MLR
- Model Selection
- Diagnostics for MLR
Readings
- Lesson Learning Objectives
- Lesson Learning Objectives
- Week 3 Suggested Readings and Exercises
- Week 3 Lab Instructions (RStudio)
- Week 3 Lab Instructions (RStudio Cloud)
- Project Instructions, Data files, and Checklist 2h
Assignments
- Week 3 Practice Quiz
- Week 3 Quiz
- Week 3 Lab