Predictive Modeling with Tidymodels in R
90 LearnersCourse for Beginner Level
1 modules
Interactive environment
9 chapters
AI Assistant
9 assignments
Shareable CertificateWhat you will learn
Course content
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Gain a solid understanding of R, one of the most widely used languages for data analysis. Explore fundamental data types and one-dimensional values, then advance to multi-dimensional structures, including matrices, data frames, and lists. Build the skills needed to apply R effectively in statistical analysis and data-driven decision-making.
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Gain practical experience in data analysis with R by learning how to clean, transform, and visualize datasets. Explore essential workflows such as selecting and filtering data, handling missing values, and summarizing results. Build confidence in preparing data for insights, reporting, and deeper statistical exploration.
TEST R COURSE
R is one of the most popular programming languages among data analysts and data scientists. R has a wide community that will always help you with any problem. Also, R has tons of different packages designed to solve various problems. The language can be easily applied to statistics and data analytics problems. In the first part, you will be introduced to the very basics of R and will deal with single 1-D values of different types.
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Master the essentials of control flow in R, including conditional statements, loops, and the powerful apply family of functions. This course is designed for beginners and will guide you through practical, real-world examples to help you write efficient and readable R code.
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Master the essential data structures in R, including lists, data frames, and factors. Learn how to create, manipulate, and analyze data using R's powerful tools, with engaging explanations and real-world challenges designed for beginners.
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In the second part of R Introduction, you will learn about multi-dimensional built-in structures, such as matrices, data frames, and lists.
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Master the essential data wrangling skills in R using the Tidyverse suite of packages. This course covers importing, cleaning, transforming, and summarizing data, empowering you to prepare datasets for analysis and visualization.
R Introduction
Gain a solid understanding of R, one of the most widely used languages for data analysis. Explore fundamental data types and one-dimensional values, then advance to multi-dimensional structures, including matrices, data frames, and lists. Build the skills needed to apply R effectively in statistical analysis and data-driven decision-making.
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Gain practical experience in data analysis with R by learning how to clean, transform, and visualize datasets. Explore essential workflows such as selecting and filtering data, handling missing values, and summarizing results. Build confidence in preparing data for insights, reporting, and deeper statistical exploration.
TEST R COURSE
R is one of the most popular programming languages among data analysts and data scientists. R has a wide community that will always help you with any problem. Also, R has tons of different packages designed to solve various problems. The language can be easily applied to statistics and data analytics problems. In the first part, you will be introduced to the very basics of R and will deal with single 1-D values of different types.
Control Flow in R
Master the essentials of control flow in R, including conditional statements, loops, and the powerful apply family of functions. This course is designed for beginners and will guide you through practical, real-world examples to help you write efficient and readable R code.
Working with Data Structures in R
Master the essential data structures in R, including lists, data frames, and factors. Learn how to create, manipulate, and analyze data using R's powerful tools, with engaging explanations and real-world challenges designed for beginners.
R Introduction: Part II
In the second part of R Introduction, you will learn about multi-dimensional built-in structures, such as matrices, data frames, and lists.
Data Wrangling with Tidyverse in R
Master the essential data wrangling skills in R using the Tidyverse suite of packages. This course covers importing, cleaning, transforming, and summarizing data, empowering you to prepare datasets for analysis and visualization.
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