Data Analytics with R Online Training

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Data Analytics with R training will help you gain expertise in R Programming, Data Manipulation, Exploratory Data Analysis, Data Visualization, Data Mining, Regression, Sentiment Analysis and using R Studio for real life case studies on Retail, Social Media.


Data Analysis with R Programming is a comprehensive course that provides a good insight into the latest and advanced features available in different formats.It explains in detail how to perform various data analysis functions using R Programming.The course has plenty of resources that explain how to use a particular feature, in a step-by-step manner.The volume of data that one has to deal has exploded to unimaginable levels in the past decade, and at the same time, the price of data storage has systematically reduced.

Did you know?

1.R analytics (or R programming language) is a free, open-source software used for all kinds of data science, statistics, and visualization projects. ... R also allows you to build and run statistical models using Sisense data, automatically updating these as new information flows into the model.
2.R is a fast growing open source contestant to commercial software packages like SAS, STATA and SPSS. The demand for R skills in the job marketing is rising rapidly, and recently companies such as Microsoft pledged their commitment to R as a lingua franca of Data Science.

Why learn and get certified in Python?

1. The Data Science with R programming certification training covers data exploration, data visualization, predictive analytics, and descriptive analytics techniques with the R language. You will learn about R packages, how to import and export data in R, data structures in R, various statistical concepts, cluster analysis, and forecasting.
2.After successful completion of the Data Science with R certification training, you will be awarded the course completion certificate from Simplilearn.
3. There are multiple ways for R to be deployed today across a variety of industries and fields. One common use of R for business analytics is building custom data collection, clustering, and analytical models.


There are no prerequisites for this Data Science with R certification course. If you are a beginner in Data Science, this is one of the best courses to start with.

Who should attend this Training?

This certification is highly suitable for a wide range of professionals either aspiring to or are already in the IT domain, such as:
1.Individuals from any domain who possess logical thinking about mathematical and analytical skills
2.People who are working on business intelligence tools, data warehousing, and reporting tools.
3. Statisticians, Economists, Mathematicians
4. Software programmers
5.Business analysts
6.Six Sigma Consultants
7. Digital Marketing professionals

How will I perform the practical sessions in Online training?

For online training, US GlobalSoft provides the virtual environment that helps in accessing each other’s system. The detailed pdf files, reference material, course code are provided to the trainee. Online sessions can be conducted through any of the available requirements like Skype, WebEx, GoToMeeting, Webinar, etc.

Data Analytics with R Syllabus

Data Analytical With R
Module 1 : What is Data Analytics

    1. R tools and their uses in Business Analytics
    2. Objectives
    3. Analytics
    4. Where is analytics applied?
    5. Responsibilities of a data scientist
    6. Problem definition
    7. Summarizing data
    8. Data collection

Module 2 : About R:

    1. Difference between R and other analytical languages
    2. Different data types in R
    3. Built in functions of R: seq(), cbind (), rbind(), merge().
    4. Subsetting methods
    5. Use of functions like str(), class(), length(), nrow(), ncol(),head(), tail()

Module 3 : Data manipulation in R

    1. Steps involved in data cleaning
    2. Problems and solutions for Data cleaning
    3. Data inspection
    4. Use of functions grepl(), grep(), sub()
    5. Use of apply() function
    6. Coerce the data

Module 4 : Data Import techniques

    1. How R handles data in a variety of formats
    2. Importing data from csv files, spreadsheets and text files
    3. Import data from other statistical formats like sas7bdat and sps
    4. Packages installation used for database import
    5. Connect to RDBMS from R using ODBC and basic SQL queries in R
    6. Basics of Web Scraping

Module 5 : Exploratory Data analysis

    1. Understanding the Exploratory Data Analysis(EDA)
    2. Implementation of EDA on various datasets
    3. Boxplots
    4. Understanding the cor() in R
    5. list()
    6. Multiple packages in R for data analysis
    7. Segment plot HC plot in R

Module 6 : Data Visualization in R

    1. Understanding on Data Visualization
    2. Graphical functions present in R
    3. Plot various graphs like tableplot
    4. Histogram
    5. Box Plot
    6. Customizing Graphical Parameters to improvise the plots
    7. Understanding GUIs like Deducer and R Commander
    8. Introduction to Spatial Analysis

Module 7 : Data Mining: Clustering Techniques

    1. Introduction to Data Mining
    2. Understanding Machine Learning
    3. Supervised and Unsupervised Machine Learning Algorithms
    4. K-means Clustering

Module 8 : Data Mining: Association Rule Mining and Sentiment Analysis

    1. Association Rule Mining
    2. Sentiment Analysis

Module 9 : Linear and Logistic Regression

    1. Linear Regression
    2. Logistic Regression

Module 10 :Anova
Module 11 : Predictive Analysis
Module 12 :More on Data Mining

Prepare for Certification

Our training and certification program gives you a solid understanding of the key topics covered on the Oreilly’s Data Analytics Certification. In addition to boosting your income potential, getting certified in Data Analytics demonstrates your knowledge of the skills necessary to be a successful Data Analytics Developer. The certification validates your ability to produce reliable, high-quality results with increased efficiency and consistency.