Datacamp – Data Scientist with R 2023-11
Datacamp – Data Scientist with R 2023-11 Downloadly IRSpace
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Data Scientist with R, Learn how to use R for data science, from data manipulation to machine learning, and gain the career-building R skills you need to succeed as a data scientist. As you progress through the courses in this track, you’ll explore how learning data science with R can help you to import, clean, manipulate, and visualize data. R is a versatile language for any aspiring data professional or researcher, and by learning the integral skills, you’ll develop a solid foundation for your data science journey. Through interactive exercises, you’ll get hands-on with some of the most popular R packages, including tidyverse packages like ggplot2, dplyr, and readr. You’ll work with real-world datasets as you write your own functions and learn foundational statistical and machine learning techniques. Start this track, grow your R programming and data science skills, and begin your journey to becoming a confident data scientist.
What you’ll learn
- Introduction to the Tidyverse
- Data Manipulation with dplyr
- Joining Data with dplyr
- Introduction to Statistics in R
- Introduction to Data Visualization with ggplot2
- Data Manipulation with R
- Data Communication Concepts
- Introduction to Importing Data in R
- Cleaning Data in R
- Working with Dates and Times in R
- Introduction to Writing Functions in R
- Exploratory Data Analysis in R
- Introduction to Regression in R
- Sampling in R
- Hypothesis Testing in R
- Experimental Design in R
Specificatoin of Data Scientist with R
- Publisher : Datacamp
- Teacher : JONATHAN CORNELISSEN
- Language : English
- Level : All Levels
- Number of Course : 22
- Duration : 88 hours to complete the course
Content of Data Scientist with R
Pictures
Sample Clip
Installation Guide
Extract the files and watch with your favorite player
Subtitle : English
Quality: 720p
Download Links
Introduction to R
Intermediate R
Introduction to the Tidyverse
Data Manipulation with dplyr
Joining Data with dplyr
Introduction to Statistics in R
Introduction to Data Visualization with ggplot2
Intermediate Data Visualization with ggplot2
Data Communication Concepts
Introduction to Importing Data in R
Cleaning Data in R
Working with Dates and Times in R
Introduction to Writing Functions in R
Exploratory Data Analysis in R
Introduction to Regression in R
Intermediate Regression in R
Sampling in R
Hypothesis Testing in R
Experimental Design in R
Supervised Learning in R Classification
Supervised Learning in R Regression
Unsupervised Learning in R
File size
1.94 GB
