Disclosure: when you buy through links on our site, we may earn an affiliate commission.

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
4.7
4.7/5
(7,855 reviews)
55,959 students
Created by

9.6

CourseMarks Score®

10.0

Freshness

9.2

Feedback

9.1

Content

Platform: Udemy
Video: 5h 59m
Language: English
Next start: On Demand

Top R courses:

Detailed Analysis

CourseMarks Score®

9.6 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

10.0 / 10
This course was last updated on 6/2022.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

9.2 / 10
We analyzed factors such as the rating (4.7/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

9.1 / 10
Video Score: 8.5 / 10
The course includes 5h 59m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 6 hours 00 minutes of 161 R courses on Udemy.
Detail Score: 9.4 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

6 articles.
0 resource.
0 exercise.
0 test.

Table of contents

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.

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

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

How much does the R Programming: Advanced Analytics In R For Data Science course cost? Is it worth it?

The course costs $14.99. And currently there is a 82% discount on the original price of the course, which was $84.99. So you save $70 if you enroll the course now.
The average price is $18.7 of 161 R courses. So this course is 20% cheaper than the average R course on Udemy.

Does the R Programming: Advanced Analytics In R For Data Science course have a money back guarantee or refund policy?

YES, R Programming: Advanced Analytics In R For Data Science has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the R Programming: Advanced Analytics In R For Data Science course, but there is a $70 discount from the original price ($84.99). So the current price is just $14.99.

Who is the instructor? Is Kirill Eremenko a SCAM or a TRUSTED instructor?

Kirill Eremenko has created 60 courses that got 573,207 reviews which are generally positive. Kirill Eremenko has taught 2,123,163 students and received a 4.6 average review out of 573,207 reviews. Depending on the information available, Kirill Eremenko is a TRUSTED instructor.
Data Scientist
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!
Browse all courses by on Coursemarks.

9.6

CourseMarks Score®

10.0

Freshness

9.2

Feedback

9.1

Content

Platform: Udemy
Video: 5h 59m
Language: English
Next start: On Demand

Students are also interested in

Review widget (for course creators):

R Programming: Advanced Analytics In R For Data Science rating
Code for the widget (just copy and paste it to your site):
<a href="https://coursemarks.com/course/r-programming-advanced-analytics-in-r-for-data-science/" target="_blank" title="R Programming: Advanced Analytics In R For Data Science on Coursemarks.com"><img border="0" src="https://coursemarks.com/widget/96.svg" width="200px" alt="R Programming: Advanced Analytics In R For Data Science rating"/></a>