Linear regression has become an essential topic across multiple fields, including business, machine learning, statistics, data science, and deep learning. Mastering linear regression is crucial for anyone looking to build a strong foundation in these areas, and the best way to get started is by enrolling in a top-rated linear regression online course.
Whether you’re a beginner or an advanced learner, there are numerous free and paid options available to help you on your journey.
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Why Learn Linear Regression?
Linear regression is one of the most fundamental concepts in predictive analytics and data modeling. It allows you to analyze relationships between variables and make predictions based on data, which is a key skill in data science and machine learning.
Choosing the right online course is critical to ensure you gain a solid understanding of the subject. Here, we’ve compiled a list of the best linear regression online courses available in 2025, covering beginner to advanced levels.
In a Hurry?
If you’re short on time and want to quickly find the best linear regression online course, here are some top recommendations:
–Machine Learning: Regression course is the best one if you are pursuing Machine Learning or ML practitioner.
–Data Science: Linear Regression training course is the best tutorial if you’re a Data Science practitioner.
–Problem Solving with Advanced Analytics is a basic and free course to learn Linear Regression online.
–Inference for Linear Regression in R is a course to choose if your main subject falls under Probability and Statistics.
–Deep Learning Prerequisites: Linear Regression in Python, if your specialty is Deep Learning.
Course Name | Key Feature |
Beginner-friendly, covers simple and multiple regression, focuses on statistical modeling, hands-on project, 9-11 hours, Duke University course. | |
Understand Docker fundamentals by building and deploying a static web app. | |
Create Docker containers for a Flask app with Seaborn visualizations. | |
Execute Selenium tests on Docker for automated user interface testing. | |
Gain hands-on experience with Docker, from basic to advanced concepts. | |
Deploy machine learning models using TensorFlow and Docker. | |
Set up independent development environments for multiple servers. | |
Learn to create custom Docker images using Dockerfiles. | |
Master the basics of Docker, including hubs and image creation. |
FAQ on Linear Regression Online Course
1. What is Linear Regression, and why is it important to learn?
Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables. It is crucial in various fields like data science, machine learning, and business analytics because it helps in predicting outcomes based on historical data, identifying trends, and making data-driven decisions.
2. Do I need prior knowledge of statistics to learn Linear Regression?
Having a basic understanding of statistics, such as distributions, variance, and probability, is helpful but not mandatory. Many beginner-friendly courses introduce the necessary statistical concepts before diving into linear regression.
3. Which programming language is best for learning Linear Regression?
Popular programming languages used for linear regression include Python and R. Python is widely used in machine learning and data science, while R is known for its strong statistical analysis capabilities. Many courses teach linear regression using these languages, depending on the focus area.
4. Is Linear Regression only useful for data scientists?
No, linear regression is a versatile tool used in many fields beyond data science, including business analytics, finance, economics, and even healthcare. It’s valuable for anyone looking to analyze relationships between variables or make predictions based on data.
5. How long does it take to learn Linear Regression?
The time it takes to learn linear regression depends on your background and the depth of the course. Most beginner courses take around 10-20 hours to complete, while more advanced courses may take 30-50 hours or more, depending on the complexity and depth of topics covered.
Best Linear Regression Online Course
1. Linear Regression and Modeling – Coursera
This course is a beginner’s course to learn Linear Regression from scratch. It starts by explaining what linear Regression and modeling are by giving an overview of the subject. Then it continues to teach the simple and multiple linear regressions models. The models that you study in this course will allow you to evaluate the relationship between a continuous response variable and variables in a data set.
The course kicks off by teaching you the fundamentals of linear Regression and then to advanced topics. Every topic is explained by providing examples in every step. This course also helps if you are beginning to learn statistics or R programming language. Both are important topics in Data Science and Machine Learning. Best online course to learn Machine Learning might be a useful post for you.
Key takeaways of this course:
- Learn linear Regression and modeling from the beginning.
- Study the relationships between multiple variables.
- Linear models are used here to predict and evaluate relationships.
- Learn both linear Regression and Multiple Regression.
- Finish the final hands-on project to earn the certificate.
Duke University created this course, and it can be completed in about 9-11 hours. Over 56k students have enrolled in this course. It has an average rating of 4.7 out of 5. Also, check out for more hands-on projects on Linear Regression for beginners.
2. Machine Learning: Regression – Coursera
Here you will learn the linear regression topics that align with the Machine Learning subject. The University of Washington created this online Machine Learning: Regression course. It was created to teach linear Regression to students in an easy way for ML enthusiasts. Study the linear regression models to perform prediction and feature selection.
All the complex subjects are explained in easy and simple instructions. It includes a case study to Predict Housing Prices. Here you will use all the skills that you gained in this course and create and model that predicts the price of the house. This is one example of a linear regression model. You can use this model and apply it to predict similar tasks.
Key takeaways of this course:
- Learn to define the input/output of a regression model.
- Suitable course for Machine Learning practitioners.
- The techniques that you learn here can be implemented using Python.
- Learn how the model parameters can be estimated using optimization algorithms.
Over 110k learners have signed up in this course, and it can be completed with a time span of 18-22 hours. The average rating of the course is 4.8 out of 5.
3. Data Science: Linear Regression – edX
This course is the most suitable one if you are pursuing to become a Data Scientist. Harvard University created this course and offered it through Coursera. With this course, you will study the linear Regression that will be useful for Data Science. It includes video lessons, practice tests, and exercises to learn the linear regression models effectively.
In the Data Science field, it is an ordinary event to compare the relationship between two or more variables. Here you will learn to quantify the relationship between two or more variables. Then you will conclude the outcomes with the best predictions. Linear Regression is an essential topic to learn, and one must know when to apply this technique.
Key takeaways of this course:
- Learn how Galton originally developed the Linear Regression.
- Study what confounding is and learn to detect it.
- Implement linear Regression in R to determine the relationships between variables.
- A self-paced online course that needs 2-3 hours of study time per week.
- Data Science students will benefit the most from this course.
Over 69k students enrolled in this course to learn Linear Regression. This course is the best way to learn Linear Regression in the right way.
4. Regression Models – Coursera
Johns Hopkins University offers this Regression Models training course. It is designed to guide students on how to learn linear Regression. The subset of linear models is Regression models, an essential statistical analysis tool in a data scientist’s toolkit, just like scikit-learn or pandas library. It covers modern thinking on model selection and novel uses of regression models, including scatterplot smoothing.
The course has been designed to cover least squares, inference using regression models, and regression analysis. All three are essential topics on the subject. It also teaches a special case of the regression model known as ANOVA and ANCOVA. Both of these are also covered here.
Key takeaways of this course:
- Learn how you can use least squares, regression analysis, and inference.
- Explore the analysis of residuals and variability.
- Understand the concepts of both ANOVA and ANCOVA model cases.
- Describe novel uses of regression models such as scatterplot smoothing.
- Best Linear Regression course for Data Science students.
The course covers detailed and comprehensive guides on Linear Regression that amounts to over 54 hours of study time. Over 97k students enrolled in this course and have an average rating of 4.4 out of 5.
5. Linear Regression for Business Statistics – Coursera
Linear Regression Analysis is an essential Business Statistics tool used in the industry. Here you learn about the important tool of Linear Regression in the field of business. Once the introduction of linear Regression is done, you will proceed to build a Regression Model and estimate it using Excel. Hence, you may find the best course to learn Microsoft Excel useful.
The duration of the course is about 4 weeks and is a part of the Business Statistics and Analysis Specialization course. Once you go through the introductory class, you begin to learn Hypothesis Testing. Here you utilize Microsoft Excel to refine the results and get the desired result. It is a linear regression online course for business students.
Key takeaways of this course:
- Learn to make inferences using the estimated model.
- Make predictions using the Regression model.
- Perform hypothesis testing in a Linear Regression.
- You will perform the ‘Goodness of Fit’ measures and get the desired result.
- Perform mean centering of variables in a regression model.
The course has been enrolled by more than 16k students so far, and it has an average rating of 4.8 out of 5.
6. Linear Regression in R for Public Health – Coursera
This course has been developed by Imperial College London, and it is a part of Statistical Analysis with R for Public Health Specialization. Enroll in this course if you qualify for all the prerequisites of the course. You should know hypothesis testing, distributions, types of variables, p values, and confidence intervals using R.
If your career or education falls under the Public health sector, then this course is the right path for you to learn Linear Regression online. The course is designed to teach you to prepare the data, assess it, and test its underlying assumptions. Here you will use software package R to get things done.
Key takeaways of this course:
- Learn which linear regression model to use at the appropriate time.
- It provides an introduction to linear Regression and the concept of model assumptions.
- You will practice running correlations in R, which is essential to the subject.
- Learn how you can build a regression model when you have a choice.
This Linear Regression course falls under the intermediate level; hence only enroll if you qualify for the prerequisites. The average rating for the course stands at 4.8 out of 5.
7. Problem Solving with Advanced Analytics – Udacity
This beginner’s and a free course on Udacity will teach you only the fundamental topics of Linear Regression. Here you will be introduced to predictive analytics, a robust tool. With its help, you can help businesses analyze the data, predict future outcomes, and trends. All the topics are taught using the scientific approach to solve problems with data.
To take this course, you don’t need to know any programming languages. An introduction to the Alteryx tool will be provided. And you get a free license of Alteryx tool if you further enroll in their Nanodegree program. This course is suitable for anyone who is pursuing a career in business analysis.
Key takeaways of this course:
- Learn to apply the framework that us useful to solve a business problem.
- Identify which analytical method can be applied to a given problem.
- It doesn’t need any programming or coding experience.
- Includes a project based on the principles learned in this course.
The course contains 3 lessons and would take about 2 weeks to complete—the best free course to learn the fundamentals of linear Regression.
8. Inference for Linear Regression in R – DataCamp
Inference for Linear Regression in R offers you a chance to think about other many samples that are able to produce different linear models. Here you learn to perform inference using linear models. The packages learned in this course include ggplot2, dplyr, and broom package. All the packages are essential in learning Linear Regression.
The course has two prerequisites, Foundations of Inference and Multiple and Logistic Regression in R. The course contains 5 chapters where you get the first chapter for free. Take the free Chapter course and see how good the courses are before becoming a member of DataCamp. It also comes with 59 exercises for you to work on.
Key takeaways of this course:
- Learn what hypothetical population is in linear Regression.
- Using simulation methods for regression models study the sampling distribution.
- Includes 4 hours of video and 59 exercises for enhanced learning of linear Regression.
- The first chapter is always free to learn the fundamentals.
The course has over 6k learners and comes with a total duration of 4 hours of video lessons. However, the real gem in this course is the number of exercises it offers, 59.
9. Deep Learning Prerequisites: Linear Regression in Python – Udemy
This course is for Deep Learning students to learn Linear Regression using Python. The requirement to take this Linear Regression course is that you should know derivatives using calculus and Python programming. If you lack Python skills, you can learn Python fast. The techniques taught here are useful for Data Science, Machine Learning, and Statistics.
Once the theory part of the course is complete, it dives deep to write a code to the linear regression module in Python. It is one of the best introductory courses to learn everything about Linear Regression. You also get the hang of Moore’s Law. It also shares many tips and tricks that will be useful for you for more years to come. Some of the best online course for deep learning is useful for you.
Key takeaways of this course:
- Learn to derive and solve a linear regression model.
- One of the best seller course in Udemy to learn Linear Regression.
- You will be able to program your own version of a linear regression model using Python programming language.
- It comes with 6 hours of video content with lifetime access.
The course can be taken by anyone who qualifies for the requirements. It is one of the best-seller courses on Udemy to learn Linear Regression.
Summary
Whether you are a beginner looking to get started or an experienced professional aiming to deepen your knowledge, these courses offer a wide range of learning paths tailored to your specific needs. Enroll in one of these top linear regression online courses today and take the next step toward mastering one of the most critical skills in data science, machine learning, and business analytics.
If you have any questions or need further recommendations, feel free to leave a comment or share this guide with others interested in learning linear regression online!
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