Introduction to R Programming
Providing you with the skills to manipulate, analyze, and visualize data with the best programming language for statistical analysis for data science.
With Simona Dobreva and Iliya ValchanovStart Course
R is one of the best programming languages specifically designed for statistics and graphics. Programming in R is a fast and effective way to perform advanced data analyses and manipulations. In this course, you will learn how to use R and utilize the many data analysis techniques, methods, and functions it has to offer to the professional data scientist.
Skills you will gain
What You'll Learn
Here, you will learn how to work on statistics and graphics with R. Become a professional data scientist by applying specific R techniques, methods, and functions.
- Introduction & Getting Started Free6 Lesson 24 Min
- The building blocks of R Free8 Lesson 33 Min
- Vectors and vector operations Free7 Lesson 29 Min
- Matrices Free10 Lesson 48 Min
- Fundamentals Of Programming With R Free10 Lesson 43 MinRelational operators in R Free Logical operators in R Free Logical operators and vectors Free If else else-if statements Free If else else-if keep-in-minds's Free For loops in R Free While loops in R Free Repeat loops in R Free Building a function in R 2.0 Free Building a function in R 2.0 Scoping Free
- Data frames in R Free10 Lesson 36 MinWhat does section 6 cover Free Creating a data frame Free The Tidyverse package Free Data import into R Free Importing a CSV into R Free Data export in R Free Getting a sense of your data frame Free Indexing and slicing a data frame in R Free Extending a data frame in R Free Dealing with missing data Free
- Manipulating data with R Free7 Lesson 25 MinWhat does section 7 cover Free Data transformation with R - the Dplyr package - Part I Free Data transformation with R - the Dplyr package - Part II Free Sampling data with the Dplyr package Free Using the pipe operator Free Tidying your data - gather() and separate() Free Tidying your data - unite() and spread() Free
- Visualizing data with R Free8 Lesson 42 Min
- Exploratory data analysis with R Free5 Lesson 25 Min
- Hypothesis Testing Free9 Lesson 56 MinDistributions Free Standard Error and Confidence Intervals Free Hypothesis Testing Free Type I and Type II errors Free Test for the mean. Population variance known Free The P-value Free Test for the mean. Population variance unknown Free Dependent samples Free Comparing two means. Independent samples Free
- Linear Regression Analysis in R Free7 Lesson 25 Min
“Learning R programming is a valuable asset to get you where you want to be in your data science career. In this course, I have drawn from years of experience in data analysis and have summarized all in a fast and effective training. I will be super proud and happy to share my R journey with you! ”
Worked at 365 Data Science
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Introduction to R Programming
With Simona Dobreva and Iliya Valchanov