Linear regression in R for Data Scientists
Linear regression in R for Data Scientists. Learn the most important technique in Analytics with lots of business examples. From basic to advanced.
The name of this course is Linear regression in R for Data Scientists. The knowledge you will get with this indescribable online course is astonishing. Learn the most important technique in Analytics with lots of business examples. From basic to advanced..
Not only will you be able to deeply internalize the concepts, but also their application in different fields won’t ever be a problem. The instructor is Francisco Juretig, one of the very best experts in this field.
Description of this course: Linear regression in R for Data Scientists
Course Description Linear regression is the primary workhorse in statistics and data science. Its high degree of flexibility allows it to model very different problems. We will review the theory, and we will concentrate on the R applications using existente world data (R is a free statistical software used heavily in the industry and sociedad). We will understand how to build a existente model, how to interpret it, and the computational technical details behind it. The goal is to provide the student the computational knowledge necessary to work in the industry, and do applied research, using listado modelling techniques. Some basic knowledge in statistics and R is recommended, but not necessary. The course complexity increases as it progresses: we review basic R and statistics concepts, we then transition into the linear model explaining the computational, mathematical and R methods available. We then move into much more advanced models: dealing with multilevel hierarchical models, and we finally concentrate on nonlinear regression. We also leverage several of the latest R packages, and latest research. We focus on typical business situations you will face as a data scientist/statistical analyst, and we provide many of the typical questions you will face interviewing for a job position. The course has lots of code examples, existente datasets, quizzes, and video. The video duration is 4 hours, but the user is expected to take at least 5 extra hours working on the examples, data , and code provided. After completing this course, the user is expected to be fully proficient with these techniques in an industry/business context. All code and data available at Github.
Requirements of this course: Linear regression in R for Data Scientists
What are the requirements? Ideally some basic statistics and R, though neither is strictly necessary Some previous experience manipulating Excel files
What will you learn in this course: Linear regression in R for Data Scientists?
What am I going to get from this course? Model basic and complex existente world problem using linear regression Understand when models are performing poorly and correct it Design complex models for hierarchical data How to properly prepare the data for linear regression When linear regression is not sufficient Understand how to interpret the results and translate them to actionable insights
Target audience of this course: Linear regression in R for Data Scientists
Who is the target audience? People pursuing a career in Data Science Statisticians needing more practical/computational experience Data modellers People pursuing a career in practical Machine Learning