Data Analytics with R Certification Training

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Course Highlights

  • Instructor-led Online Training
  • Project Based Learning
  • Certified & Experienced Trainers
  • Course Completion Certificate
  • Lifetime e-Learning Access
  • 24x7 After Training Support

Data Analytics with R Certification Training Course Overview

The Data Analytics with R Training offered by Multisoft Systems is an intensive course designed to equip participants with the essential skills needed to excel in the field of data science. This comprehensive program covers everything from basic data manipulation to advanced statistical analysis techniques using the R programming language. Participants will learn to handle, analyze, and visualize data effectively, turning complex datasets into actionable insights. Throughout the course, learners will engage with real-world datasets to apply theoretical concepts practically. The curriculum includes data cleaning, descriptive statistics, data visualization, and predictive analytics. Each module is structured to build on the skills learned in the previous one, ensuring a progressive learning curve. By the end of this training, participants will have mastered the use of R for data analytics tasks such as regression analysis, time series forecasting, and hypothesis testing. They will also gain the ability to create compelling data visualizations using libraries like ggplot2, enabling them to communicate findings clearly and effectively.

This course is ideal for individuals aiming to boost their career in data science, analytics, or any role that requires deep data analysis. With expert instructors and a robust learning platform, Multisoft Systems provides all the tools necessary to become proficient in data analytics with R.

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Data Analytics with R Certification Training Course curriculum

Curriculum Designed by Experts

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The Data Analytics with R Training offered by Multisoft Systems is an intensive course designed to equip participants with the essential skills needed to excel in the field of data science. This comprehensive program covers everything from basic data manipulation to advanced statistical analysis techniques using the R programming language. Participants will learn to handle, analyze, and visualize data effectively, turning complex datasets into actionable insights. Throughout the course, learners will engage with real-world datasets to apply theoretical concepts practically. The curriculum includes data cleaning, descriptive statistics, data visualization, and predictive analytics. Each module is structured to build on the skills learned in the previous one, ensuring a progressive learning curve. By the end of this training, participants will have mastered the use of R for data analytics tasks such as regression analysis, time series forecasting, and hypothesis testing. They will also gain the ability to create compelling data visualizations using libraries like ggplot2, enabling them to communicate findings clearly and effectively.

This course is ideal for individuals aiming to boost their career in data science, analytics, or any role that requires deep data analysis. With expert instructors and a robust learning platform, Multisoft Systems provides all the tools necessary to become proficient in data analytics with R.

  • Learn how to import, clean, and manipulate data using R to prepare it for analysis.
  • Gain a solid understanding of applying statistical methods for descriptive and inferential analysis in R.
  • Develop the ability to create informative and visually appealing data visualizations using R’s ggplot2 and other visualization libraries.
  • Explore basic predictive modeling techniques, including linear regression and time-series forecasting.
  • Apply R programming skills to real-world data sets, simulating scenarios that professionals face in the data analytics industry.
  • Enhance your analytical thinking by learning to approach data-related problems strategically and find effective solutions.
  • Learn to succinctly and effectively communicate statistical findings and data insights to stakeholders with varying levels of technical expertise.

Course Prerequisite

  • Familiarity with fundamental statistical concepts and methods.
  • Comfort with basic algebra and probability.
  • Proficiency in using computers and navigating software environments.

Course Target Audience

  • Data Analysts
  • Business Analysts
  • Data Scientists
  • Marketing Analysts
  • Financial Analysts
  • Research Scientists
  • Statisticians
  • IT Professionals
  • Students in technical fields
  • Professionals looking to transition into data-centric roles

Course Content

  • Introduction to terms Business Intelligence, Business Analytics, Data, Information
  • How information hierarchy can be improved/introduced
  • Understanding Business Analytics and R
  • Knowledge about the R language, its community, and its ecosystem
  • Understand the use of 'R' in the industry
  • Compare R with other software in analytics
  • Install R and the packages useful for the course
  • Perform basic operations in R using the command line
  • Learn the use of IDE R Studio and Various GUI
  • Use the ‘R help’ feature in R
  • Knowledge about the worldwide R community collaboration

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  • Various kinds of data types in R and their appropriate uses
  • Built-in functions in R like seq(), cbind (), rbind(), merge()
  • Knowledge of the various subsetting methods
  • Summarize data by using functions like: str(), class(), length(), nrow(), ncol()
  • Use of functions like head(), tail() for inspecting data
  • Indulge in a class activity to summarize data
  • dplyr package to perform SQL join in R

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  • Steps involved in Data Cleaning
  • Functions used in Data Inspection
  • Tackling the problems faced during Data Cleaning
  • Uses of the functions like grepl(), grep(), sub(), Coerce the data, uses of the apply() functions

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  • Import data from spreadsheets and text files into R
  • Import data from other statistical formats like sas7bdat and spss, packages
  • Installation used for database import
  • Connect to RDBMS from R using ODBC
  • Basic SQL queries in R
  • Basics of Web Scraping

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  • Exploratory Data Analysis(EDA)
  • Implementation of EDA on various datasets
  • Boxplots
  • Understanding the cor() in R
  • EDA functions like summarize(), llist()
  • Multiple packages in R for data analysis
  • Fancy plots like the Segment plot, and HC plot in R

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  • Data Visualization
  • Graphical functions present in R
  • Plot various graphs like tableplot, histogram, and Boxplot
  • Customizing Graphical Parameters to improvise plots
  • Understanding GUIs like Deducer and R Commander
  • Introduction to Spatial Analysis

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  • Introduction to Data Mining
  • Understanding Machine Learning
  • Supervised and Unsupervised Machine Learning Algorithms
  • K-means Clustering

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  • Association Rule Mining
  • User Based Collaborative Filtering (UBCF)
  • Item Based Collaborative Filtering (IBCF)

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  • Linear Regression
  • Logistic Regression

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  • Analysis of Variance (Anova) Technique
  • Sentiment Analysis: fetch, extract and mine live data from Twitter

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  • Decision Tree
  • Entropy
  • Gini Index
  • Pruning and Information Gain
  • Algorithm for creating Decision Trees
  • Bagging of Regression and Classification Trees
  • Random Forest
  • Working on Random Forest
  • Features of Random Forest, among others

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  • Analyze census data to predict insights on the income of the people based on the factors like age, education, work class, and occupation using Decision Trees
  • Logistic Regression and Random Forest
  • Analyze the Sentiment of Twitter data, where the data to be analyzed is streamed live from Twitter, and sentiment analysis is performed on the same

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Data Analytics with R Training (MCQ) Assessment

This assessment tests understanding of course content through MCQ and short answers, analytical thinking, problem-solving abilities, and effective communication of ideas. Some Multisoft Assessment Features :

  • User-friendly interface for easy navigation
  • Secure login and authentication measures to protect data
  • Automated scoring and grading to save time
  • Time limits and countdown timers to manage duration.
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Data Analytics with R Corporate Training

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Multisoft Systems is the “one-top learning platform” for everyone. Get trained with certified industry experts and receive a globally-recognized training certificate. Some Multisoft Training Certificate Features :

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  • Course ID & Course Name
  • Certificate with Date of Issuance
  • Name and Digital Signature of the Awardee
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Data Analytics with R Certification Training FAQ's

You will learn to manipulate data, perform statistical analysis, create predictive models, and visualize data effectively using the R programming language.

This course is designed for data analysts, business analysts, researchers, and any professional or student looking to enhance their data analysis skills using R.

Prior programming experience is helpful but not mandatory. A basic understanding of programming concepts is sufficient to start.

A computer with internet access, capable of running R and RStudio. Specific hardware specifications may be provided upon registration.

To contact Multisoft Systems you can mail us on info@multisoftsystems.com or can call for course enquiry on this number +91 9810306956

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