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Learn Data Science with R Programming (1)

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Learn Data Science with R Programming
 40 Hours
Data Science with R certification course has been designed after consulting some of the best
professionals in the industry and the faculties teaching at the best of the universities. The
reason we have done this is because we wanted to embed the topics and techniques which are
practiced in the industry, conduct them with the help of pedagogy which is followed across
universities – kind of practical data science with R implementation. In doing so, we prepare our
learners to learn data science with R programming in a more industry/job ready
fashion. IgmGuru’s Data Science with R certification course is the gateway towards your Data
Science career.
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R for Data Science Course Overview
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You would invariably find a lot of ways to learn R programming for data science from the
courses floating in the market. But what is it that makes this course stand apart from the rest. I
will give you certain points about this course and its features which will help you decide.
Welcome to R programming. R is an open-source programming language used for statistical
computing and graphics supported by the R Foundation for Statistical Computing. The R
language is widely used among statisticians and data miners for developing statistical software
and data analysis. R and its libraries are used for implementing statistical and graphical
techniques, including linear and nonlinear modeling, classical statistical tests, time-series
analysis, classification, clustering, and others. R is easily extensible through functions and
extensions, and the R community is noted for its active contributions in terms of packages
Data Science with R certification course has been designed keeping in mind about learners who
have zero to some level of exposure to R. Any ideal session in this course would dedicate a good
amount of time understanding the theoretical part after which we will be moving on to the
application of theoretical concepts by doing hands-on these statistical techniques. You would be
provided with a lot of data set to practice and implement statistical techniques during the
session and also to practice later on in the form of self-study which will help you in your journey
to learn data science with R programming.
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The three main pillars to learn data science with R programming are
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1. Application of mathematical and statistical concepts
2. Expressing them using a programming language or a tool/platform
3. Particular business domain
When learners learn data science with R programming modules, they will understand the
number of focuses that have been put on various use cases, some of the very famous
applications/services which use R, and then we gradually move to understand data science
workflow using R theoretically. We will help you understand the basic components of any data
science model, right from fetching your data from your database to building a model that is in a
deployable form.
What are the key deliverables
As you will progress in the Data Science with R certification program, you will acquire the below
skills
Introduction and implementation of Statistical techniques
Understanding the data with respect to a business problem
Data wrangling techniques
Data representation/visualization for insight generation
Understanding and building machine learning workflows
Understanding various model parameters and their role
Hyper tuning statistical models
Deploying statistical models
Maintaining statistical models
With respect to the above steps, you will also learn how to use data science specific libraries in
R e.g. Frequently used libraries in data cleaning like plyr, dplyr, tidyr, stronger, etc; data plotting
libraries like ggplot2, lattice; machine learning-based modules for building various regression
and classification based algorithms like CART, randomForest, e1071, Rpart, etc. These will help
learners to learn data science with R programming.
A good amount of content has also been dedicated to Natural Language Processing techniques
and various web scraping methodologies. Of late, NLP is gaining a lot of popularity owing to use
in our day to day life e.g. Mails, tweets, FB posts, WhatsApp chats are ideal input for any NLP
based models. You are very like to experience NLP based openings which are nowadays
considered to be a specialty within the Machine Learning branch. These are all instances that
you could experience while you learn data science with R programming.
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Hence assessing the market-based demands, we have specifically designed modules to upskill
you in this area as well – mostly to learn data science with R programming. A very significant
model in the area of NLP is Sentiment Analysis which is something we will be building to start
things of and will move on to build much complex algorithms in this area.
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Data Science with R Certification
Once you have completed the training sessions, you
will have to go through Data Science with R
certification examination. The focus will be to learn
data science with R programming modules that
learners have gone through. The certification exam
will mainly consist of quizzes, MCQs, and a project
which you will have to build from scratch and submit.
The project work would be graded after which the
certification would be awarded.
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Q : What if a class is missed?
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Q : What are the additional benefits/services which I will get once I learn R programming for data
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