 # 4 Best Linear Regression Courses

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 2019. It includes both paid and free learning resources available online to help you learn Linear Regression.

• 1. Linear Regression and Modeling from Duke University (Coursera)
• 2. Data Science: Linear Regression from Harvard University (edX)
• 3. Statistics: Linear Regression in Python (Udemy)
• 4. Data Science: Correlation and Regression (DataCamp)

### 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.

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

### 2. 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

### 3. 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 skillscan 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.

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.

– Access lecturers on any device

– Get certified in Linear Regression after completing the course

Duration: 6 Hours

Rating: 4.6 out of 5

### 4. 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 