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DevelopmentData ScienceR (programming language)

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
Rating: 4.7 out of 54.7 (7,991 ratings)
56,652 students
Created by Kirill Eremenko, Ligency I Team, Ligency Team
Last updated 8/2022
English
English, French [Auto], 

What you'll 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

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.

Who this course is for:

  • Anybody who has basic R knowledge and would like to take their skills to the next level
  • Anybody who has already completed the R Programming A-Z course
  • This course is NOT for complete beginners in R

Featured review

Shambhu Prasad Ganeshappa Aralaguppe
Shambhu Prasad G.
22 courses
7 reviews
Rating: 5.0 out of 53 years ago
Feeling awesome on completing this course, Kirill is a very inspiring person and with the videos in different parts of the world he is much more cheerful and inspiring other parts of life as well. At this point I need more practice, so repeating the lessons multiple times. The way Kirill explains the concepts and simplifies is very good. Thank you.

Instructors

Kirill Eremenko
Data Scientist
Kirill Eremenko
  • 4.6 Instructor Rating
  • 582,701 Reviews
  • 2,171,064 Students
  • 59 Courses

My name is Kirill Eremenko and I am super-psyched that you are reading this!

Professionally, I come from the Data Science consulting space with experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and since starting on Udemy I have passed on my knowledge to thousands of aspiring data scientists.

From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. One of the strongest sides of my teaching style is that I focus on intuitive explanations, so you can be sure that you will truly understand even the most complex topics.

To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you!

Ligency I Team
Helping Data Scientists Succeed
Ligency I Team
  • 4.6 Instructor Rating
  • 596,296 Reviews
  • 2,162,581 Students
  • 150 Courses

Hi there,

We are the Ligency team. You will be hearing from us when new Ligency courses are released, when we publish new podcasts, blogs, share cheatsheets and more!

We are here to help you stay on the cutting edge of Data Science and Technology. 

See you in class,

Sincerely,

Ligency Team!

Ligency Team
Helping Data Scientists Succeed
Ligency Team
  • 4.6 Instructor Rating
  • 577,679 Reviews
  • 2,162,579 Students
  • 106 Courses

Hi there,

We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more!

We are here to help you stay on the cutting edge of Data Science and Technology.

See you in class,

Sincerely,

The Real People at Ligency

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