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
The Advanced Linear Models for Data Science 1: Least Squares course helps you develop a strong foundation of linear and regression modelling. Johns Hopkins University offers the programme, and your instructors will be subject-matter experts. It is the third part of the Advanced Statistics Specialisation by Coursera.
Moreover, the course completion certificate that you will receive is shareable, after finishing the Advanced Linear Models for Data Science 1: Least Squares programme by Coursera. It will allow you to establish your relevant expertise in the field. Learn and develop fluency in the basics related to least squares and regression modelling, at your own pace.
In addition, the Advanced Linear Models for Data Science 1: Least Squares course features immersive content, developed around a self-paced model to align perfectly with your schedule. The training also provides adjustable deadlines. Furthermore, the online course allows you to quickly and efficiently start studying. You have to devote nearly 8 hours of learning time to the programme.
The Highlights
- Self-paced learning model
- Part of Advanced Statistics for Data Science Specialisation
- Advanced difficulty level
- Seven-day free trial
- Three weeks course
- Free enrolment
- A Johns Hopkins University offering
- A shareable course completion certificate
- The medium of teaching: English
- Online training
- Flexible deadlines
Programme Offerings
- self directed training
- Flexible learning
- advanced level course
- A shareable course completion certificate
- practice quizzes
- Online Course
- A Johns Hopkins University Offering
- graded assignment
- peer feedback.
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Coursera |
Coursera’s Advanced Linear Models for Data Science 1: Least Squares Course Fee Structure is :
Course | Fees in INR |
1 Month | Rs. 1,676 |
3 Months | Rs. 3,369 |
6 Months | Rs. 5,029 |
Eligibility Criteria
To enroll in the Coursera Advanced Linear Models for Data Science 1: Least Squares course, the candidate should have a basic understanding of Linear Algebra fundamentals, Calculus, Statistics, Regression model, and R programming.
Certification
Moreover, to obtain a Coursera certificate for the Advanced Linear Models for Data Science 1: Least Squares programme, you have to verify name and ID. For the certificate, you need to meet the minimum passing requirements and complete all the assignments in the curriculum. Besides, you can buy the course or request financial assistance. The deadline to get certification is 180 days, and if you fail to do so, you will need to pay again to earn the certificate.
What you will learn
After completing the Advanced Linear Models for Data Science 1: Least Squares course, you will be able to:
- Understand the mathematical concepts associated with the least-squares such as vector derivatives.
- Learn to investigate linear relationships (unconfounded) with the help of linear regression.
- Be familiar with the first, second, and third derivative of least squares.
- Develop an understanding of the analysis of covariance or ANCOVA.
- Acquire knowledge of the different design fits and matrices.
- Learn signal expansion from the decomposition of a signal.
Who it is for
Admission Details
To get enrolled in the Advanced Linear Models for Data Science 1: Least Squares course by Coursera:
- Visit the course page.
- Next, browse the website for the “Advanced Linear Models for Data Science 1: Least Squares” course, you will be taken to the course web page. Look for the “Enroll for Free” tab.
- You can enroll for free and avail of the seven-day free trial to get access to the course material. But to earn a certificate, you need to purchase the course.
- Click on “Continue” to confirm your enrolment. Post the seven days, you can proceed with buying the course upgrade.
- If you want to purchase the course, go to “My Courses” and select “Upgrade to earn a Course Certificate.” Also, if you cannot afford to buy it, you can apply for financial aid.
- Pay the fee and please save the transaction receipt.
Application Details
To enrol in the Advanced Linear Models for Data Science 1: Least Squares programme by Coursera, sign up on the website of Coursera with your Facebook/Google/Coursera account. You will get access to the free audit option to view the programme material and the seven-day free trial. Course enrolment is for free, and then you can upgrade to get a course certificate.
The Syllabus
Videos
- Introduction
- Matrix derivatives
- Coding example
- Centering by matrix multiplication
- Coding example
- Variance via matrix multiplication
- Coding example
Readings
- Welcome to the class
- Course textbook
- Grading
- In this module
Assignment
- Background Quiz
Videos
- Regression through the origin
- Centering first
- Coding example
- Connection with linear regression
- Coding example
- Fitted values and residuals
Readings
- Before you begin
- Before you begin
Assignment
- One Parameter Regression Quiz
Videos
- Least squares
- Coding example
- Prediction
- Coding example
- Residuals
- Coding example
- Generalizations
- Generalizations example
Readings
- Before you begin
- Generalizations
Assignment
- Linear Regression Quiz
Videos
- Least squares
- Coding example
- Second derivation of least squares
- Projections
- Third derivation of least squares
- Coding example
Readings
- Before you begin
Assignment
- General Least Squares Quiz
Videos
- Basic examples of design matrices and fits
- Group effects
- Change of parameterization
- ANCOVA
Assignment
- Least Squares Examples Quiz
Videos
- Bases, introduction
- Bases 2, Fourier
- Bases 3, SVDs
- Bases, coding example
- Introduction to residuals
- Partitioning variability
Assignment
- Bases Quiz
- Residuals Quiz
Instructors
Johns Hopkins Frequently Asked Questions (FAQ's)
This Coursera programme has a self-paced training model with a duration of three weeks.
For the Advanced Linear Models for Data Science 1: Least Squares, no university credits are awarded. However, certain universities may trade credits for Course Certificates.
Coursera provides financial aid to candidates who are unable to afford the course fee. To apply for financial assistance, you need to write an application and submit it on the website of Coursera.
For the Advanced Linear Models for Data Science 1: Least Squares course, you should be familiar with the fundamentals of statistics, linear algebra, calculus, and R programming.
Coursera’s Advanced Linear Models for Data Science 1: Least Squares course is best-suited to provide aspiring data scientists and biostatistics professionals with a solid foundation of relevant modeling tools. To know more, visit the Coursera website.