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R Programming for Data Science for Absolute Beginners

Posted By: lucky_aut
R Programming for Data Science for Absolute Beginners

R Programming for Data Science for Absolute Beginners
Last updated 5/2023
Duration: 5h 51m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 2.46 GB
Genre: eLearning | Language: English

Learn the art of R programming for Data Science . Learn to analyse and Visualize for Actionable Insights.

What you'll learn
R programming from Beginning to Advance.
Data Visualizations using ggplot and Base plots
When , which and how to plot for Inferences
Learn to plot scatter , bar chart , histograms, time-series
Create and access R objects - vectors,list,factors, dataframes , matrices
Learn to write conditions, loops and functions
Upload real world data like bank marketing data with 45,000 records
Requirements
Must be passionate about Data
Description
**** Reviews****
I m gaining great new skills with this course. I had no exp in R , now I m gaining confidence . Recommended for the beginners
- Myint Htoo
**** Lifetime access to course materials . 100% money back guarantee ****
If you are an absolute beginners in R , then this is the place .
Learn R program right from the basic to intermediate and advance level.
Learn how to do data visualizations on all kind of data sets.
Create and access various R datatypes and objects like vectors,factors and dataframes.
Create your own functions , loops and conditions.
Work on various plots : scatter , box plots , histograms, bar charts and derive the business and actionable insights.
Upload real world data like bank marketing data with 45,000 records
Create and access R objects - vectors,list,factors, dataframes , matrices
Do various mathematical operations on dataframes , vectors , list and other R objects.
When , which and how to plot for Inferences
Learn to write conditions, loops and functions
Case Study Include:
Identify which customers are eligible for credit card issuance
-> Use R functions , loops and apply R knowledge gained to resolve the real world problem
Root Cause Analysis of Uber Demand Supply Gap
->Understand business problems.
->Upload Uber Datasets ( drop time, pickup time, driver ID , destination , pickup point )
->Do the data visualizations and find the various insights from the datasets
-> Prepare PPT for the company CEO and other stakeholders.

Who this course is for:
Beginners who are looking to enhance their data science skills

More Info