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R Programming: Advanced Analytics In R For Data Science

Take Your R & R Studio Skills To The Next Level. Data Analytics, Data Science, Statistical Analysis in Business, GGPlot2

4.72 / 5.0
55696 students5 hours 59 minutes

Created by Kirill Eremenko, offered on Udemy

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Student feedback

9.4/10

To make sure that we score courses properly, we pay a lot of attention to the reviews students leave on courses and how many students are taking a course in the first place. This course has a total of 55696 students which left 7805 reviews at an average rating of 4.72. Impressive!

Course length

9/10

We analyze course length to see if courses cover all important aspects of a topic, taking into account how long the course is compared to the category average. This course has a length of 5 hours 59 minutes, which is pretty short. This might not be a bad thing, but we've found that longer courses are often more detailed & comprehensive. The average course length for this entire category is 7 hours 54 minutes.

Overall score

9.2/10

This course currently has a bestcourses score of 9.2/10, which makes it a great course to learn from. On our entire platform, only 15% of courses achieve this rating!

Description

Ready to take your R Programming skills to the next level?

Want to truly become proficient at Data Science and Analytics with R?

This course is for you!

Professional R Video training, unique datasets designed with years of industry experience in mind, engaging exercises that are both fun and also give you a taste for Analytics of the REAL WORLD.

In this course, you will learn:

  • How to prepare data for analysis in R

  • How to perform the median imputation method in R

  • How to work with date-times in R

  • What Lists are and how to use them

  • What the Apply family of functions is

  • How to use apply(), lapply() and sapply() instead of loops

  • How to nest your own functions within apply-type functions

  • How to nest apply(), lapply() and sapply() functions within each other

  • And much, much more!

The more you learn, the better you will get. After every module, you will have a robust set of skills to take with you into your Data Science career.


We prepared real-life case studies.

In the first section, you will be working with financial data, cleaning it up, and preparing for analysis. You were asked to create charts showing revenue, expenses, and profit for various industries.

In the second section, you will be helping Coal Terminal understand what machines are underutilized by preparing various data analysis tasks.

In the third section, you are heading to the meteorology bureau. They want to understand better weather patterns and requested your assistance on that.

What you will learn

  • Perform Data Preparation in R
  • Identify missing records in dataframes
  • Locate missing data in your dataframes
  • Apply the Median Imputation method to replace missing records
  • Apply the Factual Analysis method to replace missing records
  • Understand how to use the which() function
  • Know how to reset the dataframe index
  • Work with the gsub() and sub() functions for replacing strings
  • Explain why NA is a third type of logical constant
  • Deal with date-times in R
  • Convert date-times into POSIXct time format
  • Create, use, append, modify, rename, access and subset Lists in R
  • Understand when to use [] and when to use [[]] or the $ sign when working with Lists
  • Create a timeseries plot in R
  • Understand how the Apply family of functions works
  • Recreate an apply statement with a for() loop
  • Use apply() when working with matrices
  • Use lapply() and sapply() when working with lists and vectors
  • Add your own functions into apply statements
  • Nest apply(), lapply() and sapply() functions within each other
  • Use the which.max() and which.min() functions

Requirements

  • Basic knowledge of R
  • Knowledge of the GGPlot2 package is recommended
  • Knowledge of dataframes
  • Knowledge of vectors and vectorized operations
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Frequently asked questions

  • Price: $109.99
  • Platform: Udemy
  • Language: English
  • 5 hours 59 minutes
R Programming: Advanced Analytics In R For Data Science thumbnail

bestcourses score: 9.2/10

This course is one of the best in its category!