Introduction to R Programming on Sports Data
Introduction to R Programming on Sports Data

Introduction to R Programming on Sports Data

25,00 

Introduction to R Programming on Sports Data. I want to show you how easy it is to create predictive models using sports data

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Product Description

Introduction to R Programming on Sports Data. I want to show you how easy it is to create predictive models using sports data

Description of this course: Introduction to R Programming on Sports Data

Course Description Are you interested in learning about data analysis and machine learning, but don’t know where to start? Are you interested in sports and curious to know how analytics can be applied to sports? In the game of football, are you curious as which positions are the most important (other than the quarterback)? If so, you’ve come to the right course! In this course, I will show you how easy it is to use the statistical software program R Studio in order to use data from the NFL to answer the question of which positions matter the most in the game of football! I will work you through this project so you learn about R by doing, as opposed to watching boring lectures that cover theory without any applications My hope is that going over this project will provide the interest and motivation necessary for you to answer your own statistics and data-related questions using the concepts I cover in this course. I want you to become proactive instead of just being spectators and consumers

Requirements of this course: Introduction to R Programming on Sports Data

What are the requirements? Basic understanding of programming Basic knowledge of Python (and basic knowledge of R is recommended but not required) Basic knowledge of statistics

What will you learn in this course: Introduction to R Programming on Sports Data?

What am I going to get from this course? Complete a project that uses NFL data to determine the most important positions Learn web scraping with R and Python Read xls files into R Know the basics of dataframes, along with manipulating, merging, and combining them Split data into training, validation, and test sets, along with understanding cross-validation Be aware of the problem of overfitting when generating predictive models Learn the basics of Linear regression and Lasso regression Learn the basics of Random Forests Generate data visualization using ggplot2

Target audience of this course: Introduction to R Programming on Sports Data

Additional Information

Instructor

Jerry Kim

Lectures

10

Length

1

Skill Level

All Levels

Languages

English

Includes

Lifetime access
30 day money back guarantee!
Available on iOS and Android
Certificate of Completion

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