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R Programming: Advanced Analytics In R For Data Science

(12 customer reviews)
Product is rated as #8 in category Data Science

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

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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

12 reviews for R Programming: Advanced Analytics In R For Data Science

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  1. Marc Müller

    Amazing course with good step by step explanation and examples.
    This course gives a good insight into r and helps expanding the knowledge by building step by step on experience learned in previous lessons.
    For students who want to do some extra steps, there are always good moments to pause the video, just to play around with the newly acquired knowledge.

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  2. Andrea Piccioni

    Following this course as statistician has helped me understand how to progress in the learning processof powerful featuresof R, because Kirill is effective at exposing the programmer perspective into the explanations.
    Well done!
    oh,.. and the final video was really a great idea, Kirill.
    Thanks a lot. Wishing you all the best! (from another amazing island which is Sardinia, Italy)

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  3. Shelly Ives

    Second R course I’ve taken with him and he did not disappoint. Great examples, easy to follow. I learned a lot, Thank You!

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  4. Sidharth Pahuja

    This course is well-paced, and teaches all concepts brilliantly. Thank you for very much for this course!

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  5. Treva Etsitty

    I decided to take this course to build on what I learned from the Google data analytics certificate. There was a course within that introduced R programming with concepts such as ggplot2. This course expanded my understanding of R.

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  6. Kate Farley

    Really enjoyed this course, however I wish it had included “homework” like Kirrill’s beginner R course did

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  7. Monson Marukatat

    Very good as usual. I like the approach of learning by doing exercises that are relevant to the real world. The course design is logical and step-by-step so that it needs an incremental effort to put in. What I hope to improve is the update to the current R version as some of the real output is not per the video. In addition, I’d love Kirill to explain a little bit more about the big-picture concept such as why we should use the list in R, as opposed to normal data frame, the way some syntax is organized, for instance – lapply(Weather, “[“, 1, 7) – why the “[“.

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  8. Tanya Singh

    I really enjoyed this course. It really built on my R fundamentals and showed me how powerful R can be to analyze data.

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  9. Adefisayo Adedoyin

    The course is awesome, Kiril made the complex looks simple. Just what in I need.

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  10. Sylvina da Silva Fernandes

    Very good course with clear explanations and good practice material. This course is perfect if you already have some basic R knowledge, but want to clean up and speed up your coding. I initially bought this course to learn more about the apply() family of functions, but was happily surprised by the other course parts on data preparation and lists where I learned some new tips and tricks. Thank you!

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  11. George Immanuel

    Lacking practical lessons. We need more practice problems to work with instead of just going with the flow of the instructor jumping around new concepts. It would have much more interesting and worth the money had it have more practice problems

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  12. Ningombam Iroshini

    I have got a great experience through this course. Lots of love from the state Manipur, India.

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    R Programming: Advanced Analytics In R For Data Science
    R Programming: Advanced Analytics In R For Data Science

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