With so many Linear Regression courses, students find it extremely difficult to meet their needs. Learners often ask if there is a Linear Regression course for each case. The response is YES. Below are popular courses available. Registering for the right course is an important factor in your career progression. In this article, the best Linear Regression courses were selected by experts in 2020.
The main aim is to illustrate the best known courses in every category.
Select one that best suits your needs, based on your preference.
However, let’s look at the best Linear Regression courses on the market.
Duration: 8 weeks, 1-2 hours/week
Rating: 4.5 out of 5
Linear regression is typically used to evaluate the relationship between two or more variables. This Linear Regression course offered by Harvard University teaches you how to apply linear regression and how to correct for uncertainty in practice with R. According to our experts, this is an excellent course for those who want to know the most popular data science statistical modelling approaches. Let us tell you exactly, why. Instructor Rafael Irizarry is one of Harvard University ‘s top professors in biostatistics. He has over 15 years of teaching experience in data processing and applied statistics. After this course, you will explore uncertainty and where international variables influence the relationship between two or more other variables.
- Know how the Galton linear regression originally developed.
- A basic level tutorial about how to use R in linear regression.
- Learn from Harvard University ‘s best data science mentor.
- Easy to understand at no cost. However, after the test is completed, you can upgrade the course to $49 for graded assignments and certification.
- Get information about what to use and how to apply linear regression.
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Duration: 4 weeks, 5-7 hours/week
Rating: 4.7 out of 5
We will begin by saying this is the easiest Linear Regression course for beginners available online, which implements easy and multiple linear regression models. In this program, you will have the opportunity to know the fundamental theory behind linear regression. You will also learn how to use regression models to examine relationships among multiple variables, using data examples. The teacher Mine Cetinkaya-Rundel is one of the best practicum assistant professors at Duke University’s Department of Statistical Science. She has completed her Ph.D. in Statistics and focuses on designing student-centered learning resources for statistical introductory courses. By the end of this course, at the beginner level, you will get a clear understanding of the Linear Regression and its models.
- Learn about Linear Regression and its models for predicting a linear relationship between the two numerical variables
- Learn from one of Duke University ‘s top teachers
- Inferences for multiple linear regression, model selection, and model diagnostics will also be learned.
- One of Linear Regression course’s simplest and easiest to understand, available online for beginners.
- Explore multiple regression that allows you to model multiple predictors of the numerical response variables.
- Having completed the course and peer review task, receive shareable certificates.
- Work on tasks for the data analysis to test the linear regression expertise.
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Duration: 4 Hours, 18 Videos
Rating: 4.5 out of 5
DataCamp is known for providing individuals with some of the best online courses, and one such course is Correlation and Regression. The course will give you a clear understanding of the multiple variables relations. Using new and more complex tools, you will get a platform to explore the data with multiple variables. This course will also clarify how to evaluate the relation between two numerical quantities. Trainer Ben Baumer is an associate professor in Smith College’s Statistical & Data Science Program. He is an American Statistical Association Accredited Certified Statistician and believes in providing information to any person who is interested in Linear Regression. You will have a strong hold on the correlation and linear regression skills after completing this course.
- Get lectures from one of Smith College ‘s top teachers.
- A fast and simple route to understanding correlation and regression.
- Understand the bivariate relationship exploration techniques.
- Learn how to graphically describe the relations between two numerical quantities.
- Explore and understand simple linear regression models’ basic concepts.
- Get knowledge of how variables can be interpreted in a regression model.
- Learn the basic correlation principles for the quantification of bivariate relationships.
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Duration: 6 Hours
Rating: 4.6 out of 5
Individuals who want to make their careers in data science, analytics, machine learning and artificial intelligence – the perfect start for them is this linear regression course offered by Udemy. Developers who want to develop their coding skills will also learn a great deal from this course. You will learn in this course the most common technique used in machine learning , data science and statistics: linear regression. We believe it is a step towards success to take this course; let us tell you why. Lazy Programmer Inc. is a full-stack software developer and data scientist. For data science he educated more than 2,00,000 students: linear regression. You should be able to understand the basic concepts of ML, Data Science, and Statistics after completing this course: Linear Regression in python.
- Fix linear regression models to apply to problems with data science.
- Understand how to improve your own data analysis work programme, in Python.
- Make the course available for life after one-time subscription
- Learn how to predict the age and weight of a patient’s systolic blood pressure using multi-dimensional linear regression.
- Get a Linear Regression certification after completing the course
- Get access to lectures on any device
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This is the list of the 4 Best Online Linear Regression Courses and Certification of 2020. They are popular and loved by many experienced Linear Regression Courses learners. You will find between these courses what you need to learn in order to continue your Linear Regression journey.