10 Best Linear Regression Courses [2021 OCTOBER] [UPDATED]

best linear regression course class certification training online

After conducting in-depth research, our team of experts has come up with this list of Best Linear Regression Tutorial, Class, Course, and Training & Certification for 2021. It includes both paid and free learning resources available online to help you learn Linear Regression.


10 Best Linear Regression Courses, Certification, Training and Tutorial Online [2021 OCTOBER] [UPDATED]

1. Linear Regression and Modeling from Duke University (Coursera)

We would start by saying that this is the easiest Linear Regression course available online for beginners, which introduces simple and multiple linear regression models. In this course, you’ll get the exposure to learn the fundamental theory behind linear regression. Also, with the help of data examples, you’ll learn how to utilize regression models to examine relationships between multiple variables. The instructor Mine Cetinkaya-Rundel is one of the best Assistant Professors of the practice at the Department of Statistical Science at Duke University. She has done her Ph.D. in Statistics and focuses on developing student-centered learning tools for introductory statistics courses. By the end of this course, you’ll get a clear understanding of Linear Regression and its models at a beginner level. You may also be interested in having a look at our compilation of Best Data Science Course and machine learning tutorials.


Key USPs:

– One of the simplest and easy to understand Linear Regression course available online for beginners.

– Learn from one of the top instructors of Duke University

– Learn about Linear Regression and its models that can be used to predict a linear relationship between two numerical variables

– Explore multiple regression that allows you to model numerical response variables with the help of multiple predictors.

– You’ll also learn inference for multiple linear regression, model selection, and model diagnostics.

– Work on data analysis assignments to test your knowledge of linear regression.

– Get shareable certificates after completing the course and peer review assignment.


Duration: 4 weeks, 5-7 hours/week

Rating: 4.7 out of 5

You can Sign up Here


Reviews: Very good course taught by Dr. Mine who is as always a very good teacher. The videos are very eloquent and easy to understand. Highly recommend it if you are looking for a basic refresher course. – PK



2. Deep Learning Foundation: Linear Regression and Statistics (Udemy)

This course will be useful in building a strong understanding of fundamental topics that form the backbone of artificial intelligence and its sub-areas. Get started with introductory terminologies followed by a statistical test, gradient descent, and logistic fitting. After this endeavor, you will be able to design and implement regression algorithms. Have a look at our compilation of Best Linear Algebra Courses.


Key USPs –

– Develop a model from scratch with real-world examples

– Learn about cost optimization and adaptive learning rates

– Discuss sample estimator, distributions, and hypothesis testing

– Look into additional mathematical and Python programming concepts in the bonus section 

– Touch upon important data science interview questions

– 44 Lectures + 3 Downloadable resources + Full lifetime access


Duration: 6.5 hours 

Rating: 4.9 out of 5

You can Sign up Here  


Review: Course was a great match. Jay has the right approach of doling out math and theory, (no matter how difficult) and then correlate it to coding. – Jonathan



3. Linear Regression and Logistic Regression in Python (Udemy)

If you are looking for a program to discuss the nook and crannies of regression model creation, check out this resource. The lessons commence by covering the basics of Python and statistics. Then the mentor delves into an overview of machine learning and techniques for preparing datasets for analysis. Finally, you can put all the components together as your model comes to life.


Key USPs –

– Set up your system by following the provided guidelines

– Explore and import data from multiple sources after various treatments

– Work with libraries like NumPy, Statsmodel, and Scikit Learn

– Gain actionable insights from the result of your algorithms

– Train and evaluate your model and identify an improvement scope

– 69 Lectures + 3 Downloadable resources + Full lifetime access


Duration: 8.5 hours

Rating: 4.7 out of 5

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4. Linear Regression and Logistic Regression using R Studio (Udemy)

If you wish to develop data analysis skills using the popular programming language R, this course is one of the top contenders available online. Build the intuition to recognize business problems that can be resolved using these analyses. Structure the data and weed out errors before beginning the training and testing process. Finally, measure the accuracy rate of the model and get an estimate of its efficiency.

Key USPs –

– Set up Jupyter environment and Python for your computer

– Perform preliminary checks with univariate and bivariate analysis

– Create dummy variables and transform them

– Attempt quizzes and identify your weak areas

– Showcase your findings graphically and gain insights

– 67 Lectures + 3 Articles + Full lifetime access


Duration: 7 hours

Rating: 4.3 out of 5

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5. Excel Analytics: Linear Regression Analysis in MS Excel (Udemy)

Through the years, Excel has been one of the most popular user choices for storing and manipulating data. In this program, you will learn to leverage the software features that help you achieve regression analytics. Explore the practical aspects of dataset evaluation and understand how and where to apply the discussed methods.  


Key USPs –

– No prior experience of the subject is needed

– Observe and recognize potential problems that can be solved with this process

– Strengthen your grip on ML topics and discuss ideas confidently with peers

– Test the efficiency level of the model

– 29 Lectures + 2 Articles + 1 Downloadable resource + Full lifetime access


Duration: 2.5 hours

Rating: 4.4 out of 5

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6. 2021 Python for Linear Regression in Machine Learning (Udemy)

Creating a solution that checks all the boxes requires multiple phases and the integration of numerous libraries. This curriculum ensures that you have an all-rounded idea of all that goes into computational modeling. You will also learn to share your insights with the team for making important corporate decisions. Don’t forget to check our list of Best MySQL Courses.


Key USPs –

– Installation guidelines for Python and Anaconda are available

– Brush up the fundamental syntax in the crash course section

– Explore the functions of libraries such as NumPy, Pandas, and Matplotlib

– Cleanse, preprocess and transform data and variables

– Interpret, and plot your observations with professional accuracy

– Interact with predictions using SHAP, YellowBrick, and LIME

– Learn about optimization techniques and feature selection

– 138 Lectures + 2 Articles + 1 Downloadable resource + Full lifetime access


Duration: 14.5 hours

Rating: 4.3 out of 5

You can Sign up Here


Review: I think the explanation is pretty crisp. You have very good teaching skills making complex topics look simple. I thought I knew everything that is required to know about Linear regression until i took this course. There is always something new that i get to learn from you.



7. Data Science: Linear Regression from Harvard University (edX)

Linear Regression is normally used to measure the relationship between two or more variables. This course of Linear Regression provided by Harvard University will teach you how to implement linear regression and adjust for confounding in practice using R. According to our team, this is an excellent course for those who want to learn the most common statistical modeling approaches in data science. Now, let’s us tell you why. The instructor Rafael Irizarry is one of the top professors of Biostatistics at Harvard University. He has more than 15 years of experience in teaching student Data analysis and applied statistics. After completing this course, you’ll be able to examine confounding and where extraneous variables affect the relationship between two or more other variables.


Key USPs:

– A basic level course to understand how to use R to implement linear regression.

– Learn from the best instructor of Data Science from Harvard University.

– Know about how Galton originally developed linear regression.

– Get information regarding when to use linear regression and how to implement it.

– Free to learn without any charges. However, you can upgrade the course for 49$ to access graded assignments and certification on passing the exam.


Duration: 8 weeks, 1-2 hours/week

Rating: 4.5 out of 5

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8. Statistics: Linear Regression in Python (Udemy)

Individuals who want to make their career in data science, statistics, machine learning, and artificial intelligence – this linear regression course offered by Udemy is the perfect start for them. Also, developers who want to enhance their coding skills can learn a lot from this course. In this course, you’ll learn the most popular technique used in machine learning, data science, and statistics: linear regression. We believe that taking this course is a step towards success; let’s tell you why. The instructor Lazy Programmer Inc. is a data scientist and full-stack software engineer. He has trained more than 2,00,000 students in data science: linear regression. After completing this course, you’ll be able to understand the basic concepts of ML, Data Science, and Statistics: Linear Regression in python. You may also want to have a look at our compilation of Best AI Courses.


Key USPs:

– Learn how to develop your own working program in Python for data analysis.

– Solve linear regression models to apply it to data science problems.

– Learn how to predict a patient’s systolic blood pressure with their age and weight by applying multi-dimensional linear regression.

– Get lifetime access to the course after one-time subscription

– Access lecturers on any device

– Get certified in Linear Regression after completing the course


Duration: 6 Hours

Rating: 4.6 out of 5

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Reviews: I found this course to be mathematically challenging. I was afraid it would be tailored to all audiences at the expense of detail and complexity. I am so pleased to be able to put my knowledge of calculus, statistics, and linear algebra to use all at once.



9. Data Science: Correlation and Regression (DataCamp)

DataCamp is known for providing some of the best online courses to individuals, and correlation and Regression is one of those courses. The course will give you a clear understanding of the relationships between multiple variables. You’ll get a platform to explore data with multiple variables using new and more complex tools. Also, this course will explain how you can determine relationships between two numerical quantities. The instructor Ben Baumer is an assistant professor in the Statistical & Data Science Program at Smith College. He is an Accredited Professional Statistician by the American Statistical Association and believes in providing knowledge to every individual who is interested in Linear Regression. After completing this course, you’ll have a strong hold on correlation and linear regression skills.


Key USPs:

– A quick and straightforward course to understand correlation and regression.

– Get lessons from one of the top professors of Smith College.

– Learn how to characterize relationships graphically between two numerical quantities.

– Understand the techniques to explore bivariate relationships.

– Know the basic concepts of correlation to quantify bivariate relationships.

– Explore and learn the basic concepts of simple linear regression models.

– Get knowledge about how to interpret the coefficients in a regression model.


Duration: 4 Hours, 18 Videos

Rating: 4.5 out of 5

You can Sign Up Here


Review: DataCamp is the top resource I recommend for learning data science.


So these were the 4 Best Big Linear Regression Tutorial, Class, Course, Training & Certification available online for 2021. Hope you found what you were looking for. Wish you a Happy Learning!