Data Analytics with R 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.

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

Download Syllabus

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

Benefits

"R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists.

The average salary for a Senior Data Scientist skilled in R is $123k (Payscale salary data)

Course Content

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
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
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
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
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
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
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
Association Rule Mining 14:26 Play
Sentiment Analysis 14:26 Play
Linear Regression 14:27 Play
Logistic Regression 14:27 Play
Anova 14:27 Play
Predictive Analysis 14:27 Play
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

Course Info.

Lenght
30+hours
Effort
2-3 Hours/week
Institution
Open Source
Language
English
Video Script
English

Training Options

Selfpaced 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

799
  • 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

FAQs

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.