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Are you one of the people that would like to
start
a
data science career
or are you just
fond
of
using data
for
data analysis
in your spare time or for your job? Do you use
spreadsheets
for
data cleaning
,
wrangling
,
visualization
, and
data analysis
? I think it is time to
enhance
your
hobby
or your
career path
with learning adequate skills such as
R
.
R
is s a
programming language
that enables all essential steps when you are dealing with
data
like:
importing
,
exporting
,
cleaning
,
merging
,
transforming
,
analyzing
,
visualizing
,
and
extracting insights from the data
.
Originally R began as a
free software environment
for
statistical computing
with
graphics supported
. Over the years with the rapid development of computing power and the need for tools used for
mining
and
analyzing tons
of
data
that are being generated on every step of our lives,
R
has
emerged
into something
much greater
than its original laid path. Nowadays the
R community
is
vast
, every day thousands of people start learning R, and every day new
R's libraries
are being made and released to the world. These libraries solve different users' needs because they provide different functions for dealing with all kinds of data.
If you are still not convinced to join me on a journey where foundations for your R skills will be laid, please bear with me a bit more. In this
R for Beginners course
, you will dive into essential aspects of the language that will help you escalate your learning curve. Course first gently touches the basics like:
how to
install R
and how to install R's
Integrated Development Environment
(
IDE
)
RStudio
,
then you will learn how to create your first
R script
and
R project folder
,
R
project folder
will be your baseline folder where all your
scripts
and
assignments
will be saved,
you will learn how to install different
R packages
and how to use
functions
provided with each package.
After these first steps, you will dive into sections where all major
R data structures
are presented. You will be able to:
differentiate
among each
data structure
,
use
built-in
functions
to
manipulate data structures
,
reshape
,
access elements
, and
convert R objects
,
import data
from many different sources into R's workspace and
export R objects
to different data sources.
When you will have a grasp of what R is capable of, a section devoted to
programming elements
will guide you through essential steps for writing a
programming code
that can execute
repetitive tasks
. Here you will master:
your
first loops
,
conditional statements
,
your
custom
made functions
,
and you will be able to
optimize
your
code
using
vectorization
.
It is said that a picture can tell an observer a powerful story and holds a stronger message than a thousand words combined. In the final section of this course, the
greatest R's power
is revealed, the power to tell the story by using
data
visualization
. Here you will master how to build:
scatterplots
,
line charts
,
histograms
,
box plots
,
bar charts
,
mosaic plots
,
how to alter R's default
graphical parameters
to make
beautiful figures
,
and how to
export
a
figure
from R to a proper format for further sharing with your colleagues.
If you are still not convinced to start learning R, I will share with you how the course is structured:
Each
section
holds
separate exercises
covering learning material that is related to the
section's topic
.
Normally each exercise begins with a
short intro
that provides a
basic understanding
of the topic, then a
coding exercise
is presented.
During coding exercise, you will write the
R code
for executing given tasks.
At the end of each section, an
assignment
is presented.
Each assignment
tests
the
skills
you have
learned
during a given section.
In the last two assignments, you will write a code to build a
simulation environment
where you will execute the simulation and present the results with proper visualization techniques.
Do not lose more time and please enroll in the course today. I guarantee you will learn a lot and you will enjoy the learning process.
