Data Analytics with R Programming Certification Training

BY
Edureka

Join Edureka’s Data Analytics with R Programming Certification Training to master and become a skilled analytics professional.

Mode

Online

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study, Virtual Classroom
Mode of Delivery Video and Text Based
Frequency of Classes Weekends

Course overview

Edureka’s Data Analytics with R Programming Certification Training course imparts the necessary skills and knowledge of a fluent analytics professional. Hence, the curriculum will help you learn core topics such as collaborative filtering, data mining, sentiment analysis, data visualisation, exploratory data analysis, regression, etc. You will also establish the command of using the R Studio for real-time case studies on social media and retail.

The Data Analytics with R Programming Certification Training curriculum features instructor-led live online classes, practical assignments, a 24x7 online support, a community forum for peer interaction, and immersive project work. These will enable you to undergo an interactive and fruitful learning journey, establishing a firm foundation of Data Analytics with R. 

Once you complete all the lessons, project work, and case studies, you will receive the Data Analytics with R Programming Certification Training. The accreditation will help you showcase your acquired skills and pursue employment profiles in coveted organisations. Besides, Edureka will also provide a ‘resume builder tool’ with your e-learning LMS to help you form a robust resume and ace recruitment. 

The highlights

  • Placement assistance
  • Expert instructors
  • Instructor-led classes
  • Online LMS
  • Pre-recorded videos 
  • 24x7 support team 
  • Lifetime access to the LMS
  • Assignments every class
  • Real-life case studies
  • 30 hours of online sessions 
  • Community forum 
  • Data Analytics with R certificate
  • Project work
  • Self-paced learning

Program offerings

  • 30 hours of online classes
  • Instructor-led sessions
  • Placement assistance
  • Community forum
  • Lifetime lms access
  • Self-paced course
  • Completion certificate.

Course and certificate fees

certificate availability

Yes

certificate providing authority

Edureka

Who it is for

The online Data Analytics with R Programming Certification Training programme is an ideal fit for the following individuals: -

  • Professionals and students who wish to work in the analytics industry and want exposure to the cutting-edge tech to enhance their technical skillset.
  • Those who aspire to become Data analysts.
  • Professionals from Economics, Statistics, or Mathematics backgrounds, who wish to learn Business analytics.

Eligibility criteria

The Data Analytics with R Programming Certification Training by Edureka requires interested candidates to possess a basic knowledge of Statistics. Additionally, Edureka provides the “Statistics Essentials for R” complimentary programme to help you polish up your Statistics skills and undertake this course efficiently. 

What you will learn

Business analytics knowledge Data science knowledge R programming Machine learning

After finishing the online Data Analytics with R Programming Certification Training certification syllabus, you will achieve proficiency in the following: -

  • Understanding the concepts of business analytics and business intelligence.
  • Performing Analysis of Variance (ANOVA).
  • Exploring Recommendation systems with functions such as item-based and user0based collaborative filtering, association rule mining, and more. 
  • Learning where to algorithms – Logistic Regression, Ensemble Techniques, Decision Trees, Support Vector Machines, etc.
  • Applying numerous techniques of supervised machine learning.
  • Working on real-life projects 
  • Using several R packages to build fancy plots.
  • Implementing unsupervised and supervised strategies of machine learning to derive business-related insights. 

The syllabus

Introducing Data Analytics

Topics
  • 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
Hands-on
  • Install R and related packages
  • R operations using command line

Introduction to R Programming

Topics
  • 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
Hands-on
  • Data Types in R
  • R Functions: seq(), cbind (), rbind(), merge(). str(), class(), length(), nrow(), ncol() head(), tail()
  • SQL joins in R

Data Manipulation in R

Topics
  • 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
Hands-on
  • Data Cleaning in R
  • Data Inspection in R
  • Data Coercion in R

Data Import Techniques in R

Topics
  • 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
Hands-on
  • Database import
  • Connect to RDBMS using R
  • SQL queries in R
  • Web Scraping in R

Exploratory Data Analysis

Topics
  • 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
Hands-on
  • EDA using R
  • cor() in R
  • Plotting fancy graphs using R

Data Visualization in R

Topics
  • 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
Hands-on
  • Graphical Functions in R
  • Customizing Plots using R
  • Spatial Analysis

Data Mining: Clustering Techniques

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

Data Mining: Association Rule Mining & Collaborative filtering

Topics
  • Association Rule Mining
  • User Based Collaborative Filtering (UBCF)
  • Item Based Collaborative Filtering (IBCF)
Hands-on:
  • Association Rule Mining
  • Recommender Engines: User Based Collaborative Filtering (UBCF) Item Based Collaborative Filtering (IBCF)

Linear and Logistic Regression

Topics
  • Linear Regression
  • Logistic Regression
Hands-on
  • Linear Regression algorithm
  • Logistic Regression algorithm

Anova and Sentiment Analysis

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

Data Mining: Decision Trees and Random Forest

Topics
  • 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
Hands-on
  • Decision Tree algorithm
  • Working of Random Forest

Project Work

Topics
  • 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
Hands-on
  • Decision Trees
  • Logistic Regression
  • Random Forest
  • Sentiment Analysis

Admission details

Interested aspirants can join Edureka’s Data Analytics with R Programming Certification Training classes by following these instructions: -

  • Visit https://www.edureka.co/data-analytics-with-r-certification-training to access the programme.
  • Scroll down to see the “Enroll Now” tab and click on it.
  • Sign up with your contact number and email ID.
  • Choose a batch of your choice, and select the “Proceed to Payment” tab.
  • Pay via your preferred mode – Mastercard, Maestro, VISA, American Express, UPI, or Net banking.
  • Once your payment is made, you can start learning. 

Filling the form

Candidates can visit the course webpage and sign up with their email ID and phone number. Next, they have to choose a preferred batch, pay the programme fees, and can then start accessing the course material. There is no application form to join the Data Analytics with R Certification Training online course.

How it helps

The R programming language is a highly in-demand tool for data analytics, owing to its flexibility, community, packages, and being open-source. As a result, professionals skilled in this language are automatically sought-after by top organisations to stay ahead of the curve. 

The Data Analytics with R programming Certification Training benefits by helping you establish a robust foundation in this subject. Mastering all its key lessons, you will become a fluent data analytics professional, securing employment in esteemed companies with handsome packages. According to experts, Senior Data Scientists hold an average salary of $123,000. 

Moreover, the course provides lifetime LMS access, pre-recorded videos, instructor-led sessions, case studies conducive to real-life, and placement assistance. 

FAQs

What system requirements does this training entail?

To successfully undertake this course, you must have a system with an i3 processor or above, and at least 4GB RAM.

What can I do if I miss a session?

If you miss any sessions or classes, you can access the recorded videos in your LMS, or attend them in another live batch.

Is there a demo session available before I enrol for the Data Analytics with R Programming Certification Training online course?

No, there are no demo sessions available for attending live classes before enrolment. However, you can check the sample class recording to understand the details.

Is placement assistance available?

Yes, Edureka provides a “resume builder tool”, which you can access via your LMS. With this, you can build a professional resume in three simple steps and ace placement rounds.

What if I face more doubts regarding the Data Analytics with R Programming Certification Training?

For further doubts/queries, you can freely contact Edureka by emailing them at sales@edureka.co. Alternatively, you can get in touch with them via 9870276457 or 18442306362. 

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