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Last updated October 10, 2020

Data Science

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56 students


<h5>We at Golive classes provide world-class Data Science course Online Training.</h5>

This Data Science with R online course offers you training in the skills needed for becoming a certified data scientist. Here, you will learn the highest demand technologies like Data Science with R, Big Data on Hadoop, SAS, and execute concepts like data exploration. Testing, Hadoop, spark, regression models, etc.

To become a Master in Data Science with R Concepts like Statistics, Standard deviation, Correlation and covariance, Outliers, Hypothesis Testing, Chi-square, T-test, Anova, Linear regression, Multiple Regression, Machine learning, R Programming, Charts and Plots, and Data Science advanced Concepts with our Practical Classes. We guarantee for your Data Science with R Online Training Success with Certification.

Data Science with R training is the statistical programming language that helps you in analyzing the data in a perfect manner. In data science, nowadays R is playing an essential role and creates a lot of scopes for exploring daily. R has four standard types such as vectors, matrices, lists, and data frames.

<h5>What is this course about?</h5>

Data Science topics such as data analysis, methods to deploy R statistical computing, important Machine Learning algorithms, and K-Means Clustering. This course also includes time-series analysis, Naïve Bayes, business analytics, and the Hadoop framework. Our curriculum is designed by industry experts based on real-time scenarios. You will get hands-on experience in Data Science by working on various real-time applications.

This course focuses on R, the open-source programming language that combines statistical modeling, big data analysis, simulation, and graphics. It is widely considered one of the most flexible—and therefore powerful—tools for data science. Experts agree that R will retain its relevance for a long time to come with public documentation for the myriad of applications that it has made possible. This data science with R online training program will cover all of the main topics that are necessary for becoming fluent in the language of R and carrying out the variety of tasks that it is used for in data science applications.

<div class=”course-list-tab”>
<ul class=”course-list-tab-icon list-unstyled first”>
<li>Become a Data Science specialist.</li>
<li>You will be able to add Data science concepts to your CV</li>
<li>Become an Data Scientist.</li>
<li>Support &amp; provide a solution for clients.</li>
<ul class=”course-list-tab-icon list-unstyled last”>
<li>Learn to implement.</li>
<li>You’ll learn how to do administration.</li>
<li>Prototype your ideas with interactions.</li>
<li>All the techniques used by Data Science Administrator</li>

<h5><strong>What are the training Objectives of Data Science online training?</strong></h5>

By the end of Data science training, you will be able to:

Understand the business intelligence and business analysis
Understand the descriptive statistics of Data analysis
Working on excel with Tableau
Understand R and data exploration to R
Create decision trees.
Gain knowledge of data collection and data mining
Know the importance of big data technologies and debugging tools
To learn running non-parametric tests

<h5><strong>Why should you learn the Data Science ?</strong></h5>

There are around 5,000+ unique job postings for data scientists every month. There is a huge requirement of around 3,00,000+ Skilled Data Scientists by the End of 2020. The average salary for a professional data scientist is about $120000 USD per annum.

<h5><strong>What are the prerequisites to learn this course?</strong></h5>

Basic knowledge in Python programming is required to learn Data Science. The following job roles will get benefited by taking up this course:

Data analysts
Business analysts
IT professionals

<h5><strong>Who should learn in this Data Science training?</strong></h5>

Basic knowledge in Python programming is required to learn Data Science. The following job roles will get benefited by taking up this course:
Data analysts
Business analysts
IT professionals
Big Data professionals
BI and Analyst professionals
Big Data statisticians
Machine Learning professionals
Predictive analysts
Information architects.

<h5><strong>What are the advantages to learn this course</strong></h5>

Advantages of Data Science

The abundance of Positions.
A Highly Paid Career.
Data Science is Versatile.
Data Science Makes Data Better.
Data Scientists are Highly Prestigious.
No More Boring Tasks.
Data Science Makes Products Smarter.

R is the data science analysis software tool for the data scientist, analyst, and statisticians – anyone who needs to make the sense of data really who can use the R for statistic analysis, visualization of data, and prediction of modeling.

R is becoming the most common language of major corporations, and a sign of its extensive flexibility is the widely different kinds of companies that use R, such as Pfizer, Bank of America, and Shell, among many others. This is further proof that R is likely to continue to be adopted by smaller companies in the future. Data Science with R online training has many job opportunities in their career as developing a single page client-side web applications. As a developer, you will be hired at an entry-level in the beginning.

<h5>Why GoliveClasess?</h5>

1.We provide training along with Real-time concepts with case studies
2.Project Explanation
3.Interview Questions
4.Resume preparation
5.Technical Assistance even after Course Completion
6.Career Guidance
7.life time video recordings Acess
8.The assistance provides in consulting and placement
9.Free other courses will be provided free of cost.

<h5>Course Curriculum:</h5>

Introduction to R

  • What is R?
  • Why R?
  • Installing R
  • R environment
  • How to get help in R
  • R Studio Overview

Understanding R data structure

  • Variables in R
  • Scalars
  • Vectors
  • Matrices
  • List
  • Data frames
  • Cbind,Rbind, attach and detach functions in R
  • Factors
  • Getting a subset of Data
  • Missing values
  • Converting between vector types

Importing data

  • Reading Tabular Data files
  • Reading CSV files
  • Importing data from excel
  • Loading and storing data with a clipboard
  • Accessing database
  • Saving in R data
  • Loading R data objects
  • Writing data to file
  • Writing text and output from analyses to file

Manipulating Data

  • Selecting rows/observations
  • Rounding Number
  • Creating string from a variable
  • Search and Replace a String or Number
  • Selecting columns/fields
  • Merging data
  • Relabeling the column names
  • Data sorting
  • Data aggregation
  • Finding and removing duplicate records

Using functions in R

  • Apply Function Family
  • Commonly used Mathematical Functions

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