Data Analytics with R Training

4.2 (1972) 6791 Learners

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.

R is the most popular data analytics tool owing to it being open-source, its flexibility, packages and community.

Learn and polish your skills in techniques such as Predictive Analytics, Association Rule Mining and create your own functions, objects and packages

Duration
30+hours
Institution
Open Source
Language
English
Video Script
English

Overview

Wissenhive's Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It covers concepts of Data Manipulation, Exploratory Data Analysis, etc before moving over to advanced topics like the Ensemble of Decision trees, Collaborative filtering, etc.

Data Analytics course at our institute will prepare you to handle complex, multifaceted projects and Data Analytics certification improves your career opportunities. Our academy also offers Data Analytics online coaching at affordable cost to the individuals who are not able to attend the classroom training. We have industry experts with great experience as trainers. Register now and prove your expertise to your potential employers.

What you will learn

Here’s what you will learn!

  • Learn to explore and visualize data and polish your skills in techniques such as Predictive Analytics, Association Rule Mining and much more
  • Derive meaning from custom created charts that are used to represent complex data, manipulate this data and create statistical models for predictive analysis
  • Learn to use R, not just as a statistical tool but to create your own functions, objects and packages

Syllabus

International industry expertise at your disposal as you deep-dive into the research topic and sector of your choice.

Course Content

What is Data Analytics? (8 Lectures)

R tools and their uses in Business Analytics

14:15 Play

Objectives

14:15 Play

Analytics

14:15 Play

Where is analytics applied?

14:15 Play

Responsibilities of a data scientist

14:15 Play

Problem definition

14:15 Play

Summarizing data

14:15 Play

Data collection

14:15 Play

About R (5 Lectures)

Difference between R and other analytical languages

14:17 Play

Different data types in R

14:17 Play

Built in functions of R: seq(), cbind (), rbind(), merge()

14:17 Play

Subsetting methods

14:17 Play

Use of functions like str(), class(), length(), nrow(), ncol(),head(), tail()

14:17 Play

Data Manipulation with R (6 Lectures)

Steps involved in data cleaning

14:18 Play

Problems and solutions for Data cleaning

14:18 Play

Data inspection

14:18 Play

Use of functions grepl(), grep(), sub()

14:18 Play

Use of apply() function

14:18 Play

Coerce the data

14:18 Play

Data Import Techniques (6 Lectures)

How R handles data in a variety of formats

14:20 Play

Importing data from csv files, spreadsheets and text files

14:20 Play

Import data from other statistical formats like sas7bdat and sps

14:20 Play

Packages installation used for database import

14:20 Play

Connect to RDBMS from R using ODBC and basic SQL queries in R

14:20 Play

Basics of Web Scraping

14:20 Play

Exploratory Data Analysis (8 Lectures)

Understanding the Exploratory Data Analysis(EDA)

14:21 Play

Implementation of EDA on various datasets

14:21 Play

Boxplots

14:21 Play

Understanding the cor() in R

14:21 Play

EDA functions like summarize()

14:21 Play

llist()

14:21 Play

Multiple packages in R for data analysis

14:21 Play

Segment plot HC plot in R

14:21 Play

Data Visualization in R (8 Lectures)

Understanding on Data Visualization

14:23 Play

Graphical functions present in R

14:23 Play

Plot various graphs like tableplot

14:23 Play

Histogram

14:23 Play

Box Plot

14:23 Play

Customizing Graphical Parameters to improvise the plots

14:23 Play

Understanding GUIs like Deducer and R Commander

14:23 Play

Introduction to Spatial Analysis

14:23 Play

Data Mining: Clustering Techniques (4 Lectures)

Introduction to Data Mining

14:25 Play

Understanding Machine Learning

14:25 Play

Supervised and Unsupervised Machine Learning Algorithms

14:25 Play

K-means Clustering

14:25 Play

Data Mining: Association Rule Mining and Sentiment Analysis (2 Lectures)

Association Rule Mining

14:26 Play

Sentiment Analysis

14:26 Play

Linear and Logistic Regression (2 Lectures)

Linear Regression

14:27 Play

Logistic Regression

14:27 Play

Anova (1 Lectures)

Anova

14:27 Play

Predictive Analysis (1 Lectures)

Predictive Analysis

14:27 Play

More On Data Mining (8 Lectures)

Decision Trees

14:29 Play

Algorithm for creating Decision Trees

14:29 Play

Greedy Approach: Entropy and Information Gain

14:29 Play

Creating a Perfect Decision Tree

14:29 Play

Classification Rules for Decision Trees

14:29 Play

Concepts of Random Forest

14:29 Play

Working of Random Forest

14:29 Play

Features of Random Forest

14:29 Play

Course Details

The open source programming language R has increased in popularity in recent years, and is now universally accepted by statisticians and data miners as the number one language for data science. R uses cutting-edge technology to manipulate data and create statistical models and charts that can be used for predictive modelling. It gives quick results and because it is open source, it is supported by a worldwide community of over two million users and developers. KnowledgeHut’s Data Analytics training will take you through the basics of this powerful language R. From the ground up, you will learn how to develop data for analysis and apply statistical measures to create data visualisations. By exploring the characteristics of data sets, you can analyse and achieve optimum results based on past data.

Is this course right for you?

Statisticians, Data Analysts, Business Analysts and professionals keen to learn more about the science and practice of data analysis using R, will benefit from this data analytics certification course.

What do you need to be familiar with?

  • Basic knowledge of a programming language such as Python or Java
  • A background in Mathematics will be beneficial

Enquiry

Training Options

Self-paced Training

299
  • Lifetime access to high-quality self-paced eLearning content curated by industry experts
  • 3 simulation test papers for self-assessment
  • Lab access to practice live during sessions
  • 24x7 learner assistance and support

Live Virtual Classes

399
  • Online Classroom Flexi-Pass
  • Lifetime access 
  • Practice lab and projects with integrated Azure labs
  • Access to Microsoft official content aligned to examination

One on One Training

Enquiry Now
  • Customized learning delivery model (self-paced and/or instructor-led)
  • Flexible pricing options
  • Enterprise grade learning management system (LMS)
  • Enterprise dashboards for individuals and teams
  • 24x7 learner assistance and support

Exam & Certification

No Exam Required.

you will be required to complete a project which will be assesd by our certified instructors. on succesful completion of the project you will be awarded a training certificate.

Data Analytics with R Training

Frequently Asked Questions

You will never miss a lecture! You can choose either of the two options:

 

  • View the recorded session of the class available in your LMS.
  • You can attend the missed session, in any other live batch.

Towards the end of the course, all participants will be required to work on a project to get hands on familiarity with the concepts learnt. You will perform predictive analyses on the provided data using R programming language. This project, which can also be a live industry project, will be reviewed by our instructors and industry experts. On successful completion, you will be awarded a certificate.

Classes are held on weekdays and weekends. You can check available schedules and choose the batch timings which are convenient for you.