CLASSES

Schedule Classes

Looking for more sessions of this class?

Talk to us

R Certification Course Overview



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.

Data Science With R Programming Training Key Features

100% Money Back Guarantee
No questions asked refund*
At Fiesttech, we value the trust of our patrons immensely. But, if you feel that this Data Science With R Programming Training does not meet your expectations, we offer a 7-day money-back guarantee. Just send us a refund request via email within 7 days of purchase and we will refund 100% of your payment, no questions asked!

100% Money Back Guarantee

  • 64 hours of Applied Learning
  • 10 real-life industry projects
  • Dedicated mentoring session from industry experts
  • Lifetime access to self-paced learning

Skills Covered

  • Business analytics
  • R programming and its packages
  • Data structures and data visualization
  • Apply functions and DPLYR function
  • Graphics in R for data visualization
  • Hypothesis testing
  • Apriori algorithm
  • kmeans and DBSCAN clustering
+ Read More

Benefits

The Big Data Analytics market is expected to reach $40.6 billion by 2023, at a growth rate of 29.7-percent. Randstad reports that pay hikes in the analytics industry are 50-percent higher than the IT industry. Learning R can help you begin a career in data science.

Designation
Annual Salary
Hiring Companies
Annual Salary
502k
702k
1102k
Min
Average
Max
Hiring Companies
Annual Salary
400k
600k
802k
Min
Average
Max
Hiring Companies

REACH OUT TO US FOR MORE INFORMATION


+91 844 844 0724

info@fiesttech.com
GO AT YOUR OWN PACE

Training Options

Explore all of our training options and pick your suitable ones to enroll and start learning with us! We ensure that you will never regret it!

Self-Paced Learning
150
  • Lifetime access to high-quality self-paced eLearning content curated by industry experts
  • 7 hands-on R projects to perfect the skills learned
  • Simulation test papers for self-assessment
  • Lab access to practice live during sessions
  • 24x7 learner assistance and support
Online Bootcamp Training
210
  • Everything in Self-Paced Learning, plus
  • 90 days of flexible access to online classes
  • Live, online classroom training by top instructors and practitioners
Corporate Training
Customized to your learning needs
  • Blended learning delivery model (self-paced eLearning and/or instructor-led options)
  • Flexible pricing options
  • Enterprise grade Learning Management System (LMS)
  • Enterprise dashboards for individuals and teams
  • 24x7 learner assistance and support

R Certification Course Curriculum

Eligibility

This Data Science with R certification training is beneficial for all aspiring data scientists including, IT professionals or software developers looking to make a career switch into Data analytics, professionals working in data and business analysis, graduates wishing to build a career in Data Science, and experienced professionals willing to harness Data Science in their fields.

Read More

Pre-requisites

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.

Read More Read Less

Course Content

Live Course

Self Paced

Course Introduction
04:34
1.001 Overview
02:45
1.002 Business Decisions and Analytics
03:32
1.003 Types of Business Analytics
01:21
1.004 Applications of Business Analytics
09:00
1.005 Data Science Overview
01:12
1.006 Conclusion
02:32
Knowledge Check
01:21
2.001 Overview
02:11
2.002 Importance of R
01:21
2.003 Data Types and Variables in R
03:32
2.004 Operators in R
03:32
2.005 Conditional Statements in R
01:21
2.006 Loops in R
04:34
2.007 R script
07:28
2.008 Functions in R
03:32
2.009 Conclusion
02:11
Knowledge Check
01:12
3.001 Overview
00:54
3.002 Identifying Data Structures
16:11
3.003 Demo Identifying Data Structures
15:00
3.004 Assigning Values to Data Structures
05:25
3.005 Data Manipulation
03:32
3.006 Demo Assigning values and applying functions
08:08
3.007 Conclusion
00:54
Knowledge Check
02:11
4.001 Overview
01:12
4.002 Introduction to Data Visualization
02:45
4.003 Data Visualization using Graphics in R
16:11
4.004 ggplot2
12:00
4.005 File Formats of Graphic Outputs
01:21
4.006 Conclusion
00:25
Knowledge Check
02:35
5.001 Overview
00:54
5.002 Introduction to Hypothesis
03:32
5.003 Types of Hypothesis
02:32
5.004 Data Sampling
04:34
5.005 Confidence and Significance Levels
01:21
5.006 Conclusion
01:12
Knowledge Check
00:54
6.001 Overview
01:12
6.002 Hypothesis Test
03:32
6.003 Parametric Test
14:32
6.004 Non-Parametric Test
08:08
6.005 Hypothesis Tests about Population Means
8:00
6.006 Hypothesis Tests about Population Variance
01:12
6.007 Hypothesis Tests about Population Proportions
01:12
6.008 Conclusion
00:54
Knowledge Check
01:12
7.001 Overview
01:21
7.002 Introduction to Regression Analysis
02:35
7.003 Types of Regression Analysis Models
01:12
7.004 Linear Regression
08:08
7.005 Demo Simple Linear Regression
01:21
7.006 Non-Linear Regression
03:32
7.007 Demo Regression Analysis with Multiple Variables
13:21
7.008 Cross Validation
03:32
7.009 Non-Linear to Linear Models
05:44
7.010 Principal Component Analysis
03:32
7.011 Factor Analysis
02:32
7.012 Conclusion
01:12
Knowledge Check
00:54
8.001 Overview
00:25
8.002 Classification and Its Types
02:32
8.003 Logistic Regression
03:32
8.004 Support Vector Machines
04:34
8.005 Demo Support Vector Machines
11:10
8.006 K-Nearest Neighbours
02:11
8.007 Naive Bayes Classifier
02:35
8.008 Demo Naive Bayes Classifier
09:00
8.009 Decision Tree Classification
09:21
8.010 Demo Decision Tree Classification
05:44
8.011 Random Forest Classification
03:32
8.012 Evaluating Classifier Models
02:45
8.013 Demo K-Fold Cross Validation
03:32
8.014 Conclusion
00:54
Knowledge Check
00:54
9.001 Overview
01:12
9.002 Introduction to Clustering
02:35
9.003 Clustering Methods
07:28
9.004 Demo K-means Clustering
11:10
9.005 Demo Hierarchical Clustering
06:07
9.006 Conclusion
01:12
10.001 Overview
02:32
10.002 Association Rule
03:32
10.003 Apriori Algorithm
09:09
10.004 Demo Apriori Algorithm
08:08
10.005 Conclusion
01:21
Knowledge Check
01:21

Please Share Contact Details

Before Downloading Syllabus

By Providing your contact details, you agree to our Privacy Policy
Contact us
(+91) 844-844-0724
(Toll Free*)
Request More Information
Self Corporate
By Providing your contact details, you agree to our Privacy Policy

Data Science With R Programming Training Exam & Certification

 

No, this R course is not officially accredited.

Yes, we provide 1 practice test as part of our Data Science with R course to help you prepare for the actual certification exam. You can try these free R Programming practice questions to understand the type of tests that are part of the course curriculum.

 Upon successful completion of the Data Science with R training and passing the exam, you will receive the certificate through our Learning Management System which you can download or share via email or Linkedin.

It will take about 40 hours to complete the R programming online course successfully.

 You can re-attempt it immediately.

FAQS

Data Science With R Programming Training Course FAQs

 R is a programming language and free software developed in 1993, made up of a collection of libraries architectured especially for data science. As a tool, R is considered to be clear and accessible.

Data Science is one of the popular career domains among professionals that offers high earning potential. It mostly comprises statistics and R is the bridging language of this domain and is widely used for data analysis. By learning R programming, you can enter the world of business analytics and data visualization. It is a must-have skill for all those aspiring to become a Data Scientist.

Anyone who is looking to get started in IT or willing to further their IT career should consider learning R. We at Fiest Tech have compiled an extensive content for Data Science beginners, along with supporting blogs and YouTube videos to help you understand the Data Science basics and importance of R in the dynamic field of data science.

 R and Python are the top languages that professionals learn to start a career in Data Science. Both languages are powerful and have their own pros and cons. So, depending on which language is used for data science projects in your organization and what can help you in the long run, you can make a choice.

 Fiest Tech also provides Data Science with Python course which builds a strong foundation in data science and imparts all the valuable skills that employers look for in a data scientist.

Related Programs

Data Science & Business Analytics Related Programs

You're almost there!

We'll be using this information for your application

Self Corporate
By Providing your contact details, you agree to our Privacy Policy