Data Science with R Course Overview

The Data Science with R Programming Course in Bangalore covers data visualization & exploration and predictive & descriptive analytics using the R language. Data Science with R Programming training in Bangalore covers all about R packages, data structures in R data import and export in R, statistical concepts, cluster analysis, and forecasting.

R Certification Training Key Features

100% Money Back Guarantee
No questions asked refund*

At Simplilearn, we value the trust of our patrons immensely. But, if you feel that this R Programming course 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!
  • 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

Benefits

The Data Science with R Programming Course in Bangalore readies you for a career in Big Data Analytics, a market growing 29.7% yearly to $40.6 billion by 2023, with analysts’ pay raises 50% higher than in IT functions. Data Science with R Programming training in Bangalore can accelerate your career.

  • Designation
  • Annual Salary
  • Hiring Companies
  • Annual Salary
    ₹302KMin
    ₹516KAverage
    ₹1023KMax
    Source: Glassdoor
    Hiring Companies
    Amazon hiring for Data Analyst professionals in Bangalore
    JPMorgan Chase hiring for Data Analyst professionals in Bangalore
    Genpact hiring for Data Analyst professionals in Bangalore
    VMware hiring for Data Analyst professionals in Bangalore
    LarsenAndTurbo hiring for Data Analyst professionals in Bangalore
    Citi hiring for Data Analyst professionals in Bangalore
    Accenture hiring for Data Analyst professionals in Bangalore
    Source: Indeed
  • Annual Salary
    ₹509KMin
    ₹1364KAverage
    ₹4200KMax
    Source: Glassdoor
    Hiring Companies
    Accenture hiring for Data Scientist professionals in Bangalore
    Oracle hiring for Data Scientist professionals in Bangalore
    Microsoft hiring for Data Scientist professionals in Bangalore
    Walmart hiring for Data Scientist professionals in Bangalore
    Amazon hiring for Data Scientist professionals in Bangalore
    Source: Indeed

Training Options

Self-Paced Learning

₹ 19,999

  • 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

₹ 21,999

  • Everything in Self-Paced Learning, plus
  • 90 days of flexible access to online classes
  • Live, online classroom training by top instructors and practitioners
  • Classes starting in Bangalore from:-
23rd Oct: Weekend Class
25th Oct: Weekday Class
Show all classes

Corporate Training

Customized to your team's 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

Data Science with R Programming training in Bangalore is great for aspiring data scientists who wish to build a Data Science career, including IT professionals or software developers who wishes to make a career switch into Data Science with R Programming training in Bangalore is also a perfect one for professionals working in data and business analysis and experienced professionals interested in getting the most of Data Science in their fields.
Read More

Pre-requisites

There are no prerequisites for this Data Science with R Programming training in Bangalore. If you are just a beginner in the Data Science field, the Data Science with R Programming course in Bangalore is one of the best courses to commence your journey.
Read More

Course Content

  • Data Science with R Programming

    Preview
    • Lesson 00 - Course Introduction

      01:31Preview
      • Course Introduction
        01:31
    • Lesson 01 - Introduction to Business Analytics

      21:06Preview
      • 1.001 Overview
        00:44
      • 1.002 Business Decisions and Analytics
        04:33
      • 1.003 Types of Business Analytics
        03:53
      • 1.004 Applications of Business Analytics
        08:57
      • 1.005 Data Science Overview
        01:29
      • 1.006 Conclusion
        01:30
      • Knowledge Check
    • Lesson 02 - Introduction to R Programming

      26:35Preview
      • 2.001 Overview
        00:31
      • 2.002 Importance of R
        05:20
      • 2.003 Data Types and Variables in R
        02:14
      • 2.004 Operators in R
        04:39
      • 2.005 Conditional Statements in R
        02:45
      • 2.006 Loops in R
        05:07
      • 2.007 R script
        01:44
      • 2.008 Functions in R
        02:58
      • 2.009 Conclusion
        01:17
      • Knowledge Check
    • Lesson 03 - Data Structures

      50:57Preview
      • 3.001 Overview
        01:04
      • 3.002 Identifying Data Structures
        13:14
      • 3.003 Demo Identifying Data Structures
        14:05
      • 3.004 Assigning Values to Data Structures
        04:51
      • 3.005 Data Manipulation
        09:23
      • 3.006 Demo Assigning values and applying functions
        07:46
      • 3.007 Conclusion
        00:34
      • Knowledge Check
    • Lesson 04 - Data Visualization

      29:40
      • 4.001 Overview
        00:29
      • 4.002 Introduction to Data Visualization
        03:03
      • 4.003 Data Visualization using Graphics in R
        18:50
      • 4.004 ggplot2
        05:14
      • 4.005 File Formats of Graphic Outputs
        01:08
      • 4.006 Conclusion
        00:56
      • Knowledge Check
    • Lesson 05 - Statistics for Data Science-I

      14:10Preview
      • 5.001 Overview
        00:21
      • 5.002 Introduction to Hypothesis
        02:06
      • 5.003 Types of Hypothesis
        03:13
      • 5.004 Data Sampling
        02:48
      • 5.005 Confidence and Significance Levels
        04:33
      • 5.006 Conclusion
        01:09
      • Knowledge Check
    • Lesson 06 - Statistics for Data Science-II

      29:55Preview
      • 6.001 Overview
        00:28
      • 6.002 Hypothesis Test
        00:47
      • 6.003 Parametric Test
        14:36
      • 6.004 Non-Parametric Test
        08:31
      • 6.005 Hypothesis Tests about Population Means
        02:09
      • 6.006 Hypothesis Tests about Population Variance
        00:45
      • 6.007 Hypothesis Tests about Population Proportions
        01:11
      • 6.008 Conclusion
        01:28
      • Knowledge Check
    • Lesson 07 - Regression Analysis

      45:04Preview
      • 7.001 Overview
        00:26
      • 7.002 Introduction to Regression Analysis
        01:11
      • 7.003 Types of Regression Analysis Models
        01:38
      • 7.004 Linear Regression
        08:59
      • 7.005 Demo Simple Linear Regression
        07:29
      • 7.006 Non-Linear Regression
        03:49
      • 7.007 Demo Regression Analysis with Multiple Variables
        13:29
      • 7.008 Cross Validation
        01:48
      • 7.009 Non-Linear to Linear Models
        02:06
      • 7.010 Principal Component Analysis
        02:45
      • 7.011 Factor Analysis
        00:26
      • 7.012 Conclusion
        00:58
      • Knowledge Check
    • Lesson 08 - Classification

      01:05:14Preview
      • 8.001 Overview
        00:31
      • 8.002 Classification and Its Types
        04:24
      • 8.003 Logistic Regression
        03:35
      • 8.004 Support Vector Machines
        04:26
      • 8.005 Demo Support Vector Machines
        11:13
      • 8.006 K-Nearest Neighbours
        02:34
      • 8.007 Naive Bayes Classifier
        02:53
      • 8.008 Demo Naive Bayes Classifier
        06:15
      • 8.009 Decision Tree Classification
        09:47
      • 8.010 Demo Decision Tree Classification
        06:25
      • 8.011 Random Forest Classification
        02:01
      • 8.012 Evaluating Classifier Models
        06:04
      • 8.013 Demo K-Fold Cross Validation
        04:09
      • 8.014 Conclusion
        00:57
      • Knowledge Check
    • Lesson 09 - Clustering

      28:10Preview
      • 9.001 Overview
        00:17
      • 9.002 Introduction to Clustering
        02:57
      • 9.003 Clustering Methods
        07:47
      • 9.004 Demo K-means Clustering
        11:15
      • 9.005 Demo Hierarchical Clustering
        05:02
      • 9.006 Conclusion
        00:52
      • Knowledge Check
    • Lesson 10 - Association

      23:13Preview
      • 10.001 Overview
        00:15
      • 10.002 Association Rule
        06:20
      • 10.003 Apriori Algorithm
        05:19
      • 10.004 Demo Apriori Algorithm
        10:37
      • 10.005 Conclusion
        00:42
      • Knowledge Check
  • Free Course
  • Math Refresher

    Preview
    • Math Refresher

      30:35Preview
      • Math Refresher
        30:35
  • Free Course
  • Statistics Essential for Data Science

    Preview
    • Lesson 01: Course Introduction

      07:05Preview
      • 1.01 Course Introduction
        05:19
      • 1.02 What Will You Learn
        01:46
    • Lesson 02: Introduction to Statistics

      18:41Preview
      • 2.01 Learning Objectives
        01:16
      • 2.02 What Is Statistics
        01:50
      • 2.03 Why Statistics
        02:06
      • 2.04 Difference between Population and Sample
        01:21
      • 2.05 Different Types of Statistics
        02:42
      • 2.06 Importance of Statistical Concepts in Data Science
        03:20
      • 2.07 Application of Statistical Concepts in Business
        02:11
      • 2.08 Case Studies of Statistics Usage in Business
        03:09
      • 2.09 Recap
        00:46
    • Lesson 03: Understanding the Data

      17:29Preview
      • 3.01 Learning Objectives
        01:12
      • 3.02 Types of Data in Business Contexts
        02:11
      • 3.03 Data Categorization and Types of Data
        03:13
      • 3.03 Types of Data Collection
        02:14
      • 3.04 Types of Data
        02:01
      • 3.05 Structured vs. Unstructured Data
        01:46
      • 3.06 Sources of Data
        02:17
      • 3.07 Data Quality Issues
        01:38
      • 3.08 Recap
        00:57
    • Lesson 04: Descriptive Statistics

      32:03Preview
      • 4.01 Learning Objectives
        01:26
      • 4.02 Mathematical and Positional Averages
        03:15
      • 4.03 Measures of Central Tendancy: Part A
        02:17
      • 4.04 Measures of Central Tendancy: Part B
        02:41
      • 4.05 Measures of Dispersion
        01:15
      • 4.06 Range Outliers Quartiles Deviation
        02:30
      • 4.07 Mean Absolute Deviation (MAD) Standard Deviation Variance
        02:52
      • 4.08 Z Score and Empirical Rule
        02:14
      • 4.09 Coefficient of Variation and Its Application
        02:06
      • 4.10 Measures of Shape
        02:39
      • 4.11 Summarizing Data
        02:03
      • 4.12 Recap
        00:54
      • 4.13 Case Study One: Descriptive Statistics
        05:51
    • Lesson 05: Data Visualization

      20:55Preview
      • 5.01 Learning Objectives
        00:57
      • 5.02 Data Visualization
        02:15
      • 5.03 Basic Charts
        01:52
      • 5.04 Advanced Charts
        02:19
      • 5.05 Interpretation of the Charts
        02:57
      • 5.06 Selecting the Appropriate Chart
        02:25
      • 5.07 Charts Do's and Dont's
        02:47
      • 5.08 Story Telling With Charts
        01:29
      • 5.09 Recap
        00:50
      • 5.10 Case Study Two: Data Visualization
        03:04
    • Lesson 06: Probability

      19:46Preview
      • 6.01 Learning Objectives
        00:55
      • 6.02 Introduction to Probability
        03:10
      • 6.03 Key Terms in Probability
        02:25
      • 6.04 Conditional Probability
        02:11
      • 6.05 Types of Events: Independent and Dependent
        02:56
      • 6.06 Addition Theorem of Probability
        01:58
      • 6.07 Multiplication Theorem of Probability
        02:08
      • 6.08 Bayes Theorem
        03:10
      • 6.09 Recap
        00:53
    • Lesson 07: Probability Distributions

      22:29Preview
      • 7.01 Learning Objectives
        00:52
      • 7.02 Random Variable
        02:21
      • 7.03 Probability Distributions Discrete vs.Continuous: Part A
        01:44
      • 7.04 Probability Distributions Discrete vs.Continuous: Part B
        01:45
      • 7.05 Commonly Used Discrete Probability Distributions: Part A
        03:18
      • 7.06 Discrete Probability Distributions: Poisson
        03:16
      • 7.07 Binomial by Poisson Theorem
        01:37
      • 7.08 Commonly Used Continuous Probability Distribution
        03:22
      • 7.09 Applicaton of Normal Distribution
        02:49
      • 7.10 Recap
        01:25
    • Lesson 08: Sampling and Sampling Techniques

      30:53Preview
      • 8.01 Learnning Objectives
        00:51
      • 8.02 Introduction to Sampling and Sampling Errors
        03:05
      • 8.03 Advantages and Disadvantages of Sampling
        01:31
      • 8.04 Probability Sampling Methods: Part A
        02:32
      • 8.05 Probability Sampling Methods: Part B
        02:27
      • 8.06 Non-Probability Sampling Methods: Part A
        01:42
      • 8.07 Non-Probability Sampling Methods: Part B
        01:25
      • 8.08 Uses of Probability Sampling and Non-Probability Sampling
        02:08
      • 8.09 Sampling
        01:08
      • 8.10 Probability Distribution
        02:53
      • 8.11 Theorem Five Point One
        00:52
      • 8.12 Center Limit Theorem
        02:14
      • 8.13 Recap
        01:07
      • 8.14 Case Study Three: Sample and Sampling Techniques
        05:16
      • 8.15 Spotlight
        01:42
    • Lesson 09: Inferential Statistics

      33:59Preview
      • 9.01 Learning Objectives
        01:04
      • 9.02 Hypothesis and Hypothesis Testing in Businesses
        03:24
      • 9.03 Null and Alternate Hypothesis
        01:44
      • 9.04 P Value
        03:22
      • 9.05 Levels of Significance
        01:16
      • 9.06 Type One and Two Errors
        01:37
      • 9.07 Z Test
        02:24
      • 9.08 Confidence Intervals and Percentage Significance Level: Part A
        02:52
      • 9.09 Confidence Intervals: Part B
        01:20
      • 9.10 One Tail and Two Tail Tests
        04:43
      • 9.11 Notes to Remember for Null Hypothesis
        01:02
      • 9.12 Alternate Hypothesis
        01:51
      • 9.13 Recap
        00:56
      • 9.14 Case Study Four: Inferential Statistics
        06:24
      • Hypothesis Testing
    • Lesson 10: Application of Inferential Statistics

      27:07Preview
      • 10.01 Learning Objectives
        00:50
      • 10.02 Bivariate Analysis
        02:01
      • 10.03 Selecting the Appropriate Test for EDA
        02:29
      • 10.04 Parametric vs. Non-Parametric Tests
        01:54
      • 10.05 Test of Significance
        01:38
      • 10.06 Z Test
        04:14
      • 10.07 T Test
        00:54
      • 10.08 Parametric Tests ANOVA
        03:26
      • 10.09 Chi-Square Test
        02:31
      • 10.10 Sign Test
        01:58
      • 10.11 Kruskal Wallis Test
        01:04
      • 10.12 Mann Whitney Wilcoxon Test
        01:18
      • 10.13 Run Test for Randomness
        01:53
      • 10.14 Recap
        00:57
    • Lesson 11: Relation between Variables

      18:08Preview
      • 11.01 Learning Objectives
        01:06
      • 11.02 Correlation
        01:54
      • 11.03 Karl Pearson's Coefficient of Correlation
        02:36
      • 11.04 Karl Pearsons: Use Cases
        01:30
      • 11.05 Spearmans Rank Correlation Coefficient
        02:14
      • 11.06 Causation
        01:47
      • 11.07 Example of Regression
        02:28
      • 11.08 Coefficient of Determination
        01:12
      • 11.09 Quantifying Quality
        02:29
      • 11.10 Recap
        00:52
    • Lesson 12: Application of Statistics in Business

      17:25Preview
      • 12.01 Learning Objectives
        00:53
      • 12.02 How to Use Statistics In Day to Day Business
        03:29
      • 12.03 Example: How to Not Lie With Statistics
        02:34
      • 12.04 How to Not Lie With Statistics
        01:49
      • 12.05 Lying Through Visualizations
        02:15
      • 12.06 Lying About Relationships
        03:31
      • 12.07 Recap
        01:06
      • 12.08 Spotlight
        01:48
    • Lesson 13: Assisted Practice

      11:47Preview
      • Assisted Practice: Problem Statement
        02:10
      • Assisted Practice: Solution
        09:37

Industry Project

  • Project 1

    Products rating prediction for Amazon

    Help Amazon, a US-based e-commerce company, improve its recommendation engine by predicting ratings for the non-rated products and adding them to recommendations accordingly.

    Products rating prediction for Amazon
  • Project 2

    Demand Forecasting for Walmart

    Predict accurate sales for 45 Walmart stores, considering the impact of promotional markdown events. Check if macroeconomic factors have an impact on sales.

    Demand Forecasting for Walmart
  • Project 3

    Improving customer experience for Comcast

    Provide Comcast, a US-based global telecom company, key recommendations to improve customer experience by identifying and improving problem areas that lower customer satisfaction.

    Improving customer experience for Comcast
  • Project 4

    Attrition Analysis for IBM

    IBM, a leading US-based IT company, wants to identify the factors that influence employee attrition by building a logistics regression model that can help predict employee churn.

    Attrition Analysis for IBM
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Data Science with R Course Advisor

  • Ronald van Loon

    Ronald van Loon

    Top 10 Big Data and Data Science Influencer, Director - Adversitement

    Named by Onalytica as one of the three most influential people in Big Data, Ronald is also an author of a number of leading Big Data and Data Science websites, including Datafloq, Data Science Central, and The Guardian. He also regularly speaks at renowned events.

prevNext

Data Science with R Exam & Certification

Data Science with R Programming Training in Bangalore
  • Who provides the certification?

    After you complete the Data Science with R Programming course in Bangalore, you will be given a course completion certificate from Simplilearn.

  • What do I need to do to unlock my Simplilearn certificate?

    Online Classroom:
    • You must attend one complete batch of Data Science with R Programming training in Bangalore.
    • You must complete one project
    Online Self-Learning:
    • You must complete 85% of the Data Science with R Programming training in Bangalore.
    • You must finish one project

  • How long does it take to complete the Data Science with R Programming training in Bangalore?

    It takes approximately 40 hours to successfully complete the Data Science with R Programming training in Bangalore.

  • How long is the Data Science with R certificate from Simplilearn valid for?

    The validity of the Data Science with R Programming training in Bangalore certificate from Simplilearn never expires.

  • How many attempts do I have to pass the Data Science with R certification exam?

    You have a total maximum of three attempts to pass the Data Science with R certification exam. However, through the Data Science with R Programming course in Bangalore, Simplilearn will help you with the right guidance and support to help you pass the exam.

  • If I pass the Data Science with R certification exam, when and how do I receive my certificate?

    Once you successfully go through the Data Science with R Programming training in Bangalore and crack the exam, you'll recieve the certificate via our Learning Management System. You can download the certificate or share it through email or Linkedin.

  • If I fail the Data Science with R certification exam how soon can I retake it?

    You can retry it immediately.

  • Do you provide any practice tests as part of Data Science with R Programming training in Bangalore?

    Yes, we do! We also provide a practice test as part of Data Science with R Programming training in Bangalore to help prepare you for the final certification exam. Try these free R Programming practice questions to help you better understand the kind of tests that are part of the curriculum.

R Certification Course Reviews

  • Amol B

    Amol B

    Bangalore

    Simplilearn has designed the course in a systematic manner. It has its own UI to code the programs. In fact, the algorithm and its applications have been done in the most logical way. Thanks, Simplilearn

  • Lavanya Krishnan

    Lavanya Krishnan

    RePM consultant, Bangalore

    My instructor Shilesh gave me a lot of hands-on training and made us use the R-platform in ways that were practical and useful. It was indeed a good course.

  • Puneeta C.

    Puneeta C.

    Student at Rajasthan Technical University, Bangalore

    Simplilearn is the best platform to provide Data Science with R programming. Its projects and assignments are amazing. Keep Learning. Thank You

  • Sabyasachi Guharoy

    Sabyasachi Guharoy

    Solution Architect - Testing at Capgemini Technology Services India Pvt., Bangalore

    I enrolled in Simplilearn for an Online Self Learning course on Data Science with R Programming. The LMS interface is very user-friendly and the course material is lucid and easy to understand. I have enjoyed my learning experience with Simplilearn

  • Ajeya Kumar

    Ajeya Kumar

    Associate Director at IHS Markit, Bangalore

    The trainer is excellent. Real-time experiences shared during training are very helpful. Overall I am very happy with the training.

  • Manish Beniwal

    Manish Beniwal

    Advisor Reporting - Global Mobility at Rio Tinto, Bangalore

    I am a Data Analyst with 7 years of work experience, but I didn't have the chance to work with Statistics like I am in this course. It's a good course even for beginners. Overall, training is very good. Thank you Simplilearn.

  • Debashis Sen

    Debashis Sen

    Researcher at S&P Capital IQ, Bangalore

    The course material of the Data Science program was well designed for beginners. The presentations were precise and to the point. The mentors in the various sessions were helpful and kept close to the basics. The examples used mirror real life scenarios, hence are very useful. Finally, the members of the CD team were truly delightful!

  • Arul Venkat

    Arul Venkat

    Statistician, Bangalore

    It was a very useful and good learning experience. I have learnt the basic statistical concepts and real-time data analysis and interpretation. Got proper knowledge of R and SAS tools. Thanks to the entire Simplilearn Team.

  • Venita Mascarenhas

    Venita Mascarenhas

    Assistant Manager - Operations Support, Projects & Quality at Oracle India Pvt. Ltd, Bangalore

    Excellent session, training is very clear and always motivates. 5 Stars!

  • Mukesh Gunwant

    Mukesh Gunwant

    Program / Project Management professional, Bangalore

    Good, I am happy that the trainer possesses a very good practical knowledge.

  • Sasidhar K V

    Sasidhar K V

    Web Developer, Bangalore

    This course is good for beginners. It gives an idea of what are the things we need to focus on to grow as a data scientist.

  • Ruchi Gupta

    Ruchi Gupta

    ILP Institute, Bangalore

    I loved the training material and the simulations tests provided by simplilearn. I loved the Flexipass, where you have the opportunity to attend same topic in multiple batches for better understanding."

  • Madhusudhan S

    Madhusudhan S

    Operations Lead at NOKIA, Bangalore

    I would like to highlight that the experience is really world class and they have supported with good guides throughout the course. Support team was very proactive and needless to say they are awesome. I moved towards course completion without hassles. Thank you Simplilearn You rock!!..

  • Sameera Kalidindi

    Sameera Kalidindi

    MIS Executive at Ericsson, Bangalore

    The trainer is simply superb, his way of explanation clarifying doubts is so clear. R programming was explained step-by-step... I am very happy with the sessions.

  • Samir Swarup

    Samir Swarup

    Associate Software Architect at UST Global, Bangalore

    I have enrolled in Data Science with R Programming at Simplilearn. I had a very good experience with them. Their response time is very fast and extremely helpful in resolving my issues. Highly recommended.

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Why Online Bootcamp

  • Develop skills for real career growthCutting-edge curriculum designed in guidance with industry and academia to develop job-ready skills
  • Learn from experts active in their field, not out-of-touch trainersLeading practitioners who bring current best practices and case studies to sessions that fit into your work schedule.
  • Learn by working on real-world problemsCapstone projects involving real world data sets with virtual labs for hands-on learning
  • Structured guidance ensuring learning never stops24x7 Learning support from mentors and a community of like-minded peers to resolve any conceptual doubts

R Certification Training FAQs

  • What is R programming?

    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.

  • Why should I learn R programming?

    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.

  • How do beginners learn R online?

    Anyone who is looking to get started in IT or willing to further their IT career should consider learning R. We at Simplilearn 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.

  • Should I learn R or Python programming for a Data Science career?

    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.

    Simplilearn 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.

  • What are the system requirements?

    You will need to download R from the CRAN website and RStudio for your operating system. These are both open source and the installation guidelines are presented in the R course curriculum.

  • Who are our instructors and how are they selected?

    All of our highly qualified R course trainers are industry Data Science experts with at least 10-12 years of relevant teaching experience. Each of them has gone through a rigorous selection process that includes profile screening, technical evaluation, and a training demo before they are certified to train for us. We also ensure that only those trainers with a high alumni rating remain on our faculty.

  • What training formats are used for this R course?

    We offer this Data Science with R training in the following formats:

    Live Virtual Classroom or Online Classroom: With online classroom training, you have the option to attend the R course remotely from your desktop via video conferencing. This format reduces productivity challenges and decreases your time spent away from work or home.

    Online Self-Learning: In this mode, you’ll receive lecture videos that you can view at your own pace.

  • What if I miss a class?

    We record the R training sessions and provide them to participants after the session is conducted. If you miss a class, you can view the recording before the next class session.

  • How do I enroll for this Data Science with R certification training?

    You can enroll in this Data Science with R certification training on our website and make an online payment using any of the following options:

    • Visa Credit or Debit Card
    • MasterCard
    • American Express
    • Diner’s Club
    • PayPal

    Once payment is received you will automatically receive a payment receipt and access information via email.

  • I’d like to learn more about this Data Science with R course. Whom should I contact?

    Contact us using the form on the right of any page on the Simplilearn website, or select the Live Chat link. Our customer service representatives can provide you with more details.

  • What is Global Teaching Assistance?

    Our teaching assistants are a dedicated team of subject matter experts here to help you get certified in R programming in your first attempt. They engage students proactively to ensure the course path is being followed and help you enrich your learning experience, from class onboarding to project mentoring and job assistance. Teaching Assistance is available during business hours.

  • What is covered under the 24/7 Support promise?

    We offer 24/7 support through email, chat, and calls. We also have a dedicated team that provides on-demand assistance through our community forum. What’s more, you will have lifetime access to the community forum, even after completion of your R training with us.

  • What is online classroom training?

    Online classroom training for R certification course is conducted via online live streaming of each class. The classes are conducted by a Data Science certified trainer with more than 15 years of work and training experience.

  • Are the training and course material effective in preparing me for the Data Science with R certification exam?

    Yes, Simplilearn’s training and course materials guarantee success with the Data Science with R certification exam.

  • *Disclaimer

    *The projects have been built leveraging real publicly available data-sets of the mentioned organizations.

  • What is the salary of a Data science and Business Analyst in Bangalore?

    In Bangalore, Karnataka, the average Income for a Data Scientist is Rs. 989932/- To get this job, the candidate should complete data science with R programming training in Bangalore.

  • What are the major companies hiring for Data science and Business Analyst in Bangalore?

    Flipkart, Accenture, IBM, Myntra, EY, Amazon, Capgemini, IQVIA, Concentric are some of the companies that are hiring for the role of Data science and business analyst in Bangalore.These companies hire the person with data science with r programming training in Bangalore.

  • What are the major industries in Bangalore?

    ABB India Ltd, BEML Ltd, Bharat Electronics Ltd, Bosch Ltd, Dell International Services India Pvt Ltd, Hindustan Aeronautics Ltd, Mangalore Chemicals & Fertilizers Ltd are some major industries in Bangalore, which hire candidates with data science with r programming training course in Bangalore.

  • How to become a Data science and Business analytics in Bangalore?

    In order to become a Data science and Business Analytics, you must first complete a data science with R programming training in Bangalore with additional set of experience and basic technical knowledge.

  • How to Find Data science and Business analytics courses in Bangalore?

    To get a job in the role of Data science and Business Analytics, you should have a certification in a data science with r programming training course in Bangalore.

  • How do I become an R Programmer?

    To become an R programmer, you need a degree in IT, Computer Science, or any allied field. After this, you can go for an R certification for more comprehensive knowledge.

  • What is R Programming used for?

    R is a programming language that is used for statistical computing graphics for cleaning, analyzing, and presenting data. By seeking an R course, you’ll get the opportunity to learn about R and its applications in detail.

  • Is the R course difficult to learn?

    This Data Science with R course is easy to learn. Anyone can pursue it, whether a fresh IT graduate or professionals like IT professionals, analytics professionals, and software developers.

  • Is R Programmer a good career option?

    R programmers are best suited for industries dealing with Data Science projects based on statistical model implementation for data analysis. They are paid quite well in the industry with a salary starting at $85,000, which may reach $122,000 with only ten years of experience (PayScale.com). Across the world, professionals with Data Science with R certification are in high demand. Presently, there are nearly 1 million R-specific job vacancies globally, making it one of the leading career options. Given this, it will be highly beneficial for you if you seek an R certification along with a degree in Data Science.

  • How do beginners learn R?

    Beginners can learn R by seeking comprehensive R training that will help them have a profound base in R and seek expert-level knowledge. Upon taking the training, they must consider working on R-based projects to gain relevant practical experience.

  • Is R certification worth it?

    Seeking this R training is worth it as it will help you:

    • Gain a basic understanding of business analytics
    • Install R, RStudio, workspace setup, and seek knowledge on the different R packages
    • Master R programming and understand how different statements are executed in R
    • Gain a deeper understanding of data structure used in R and learn how to import/export data in R
    • Define, comprehend and use the various apply functions and DPLYR functions
    • Understand and use the different graphics in R for data visualization
    • Gain a basic understanding of different statistical concepts
    • Gain understanding and know the use of the hypothesis testing method to drive business decisions
    • Understand and utilize linear and non-linear regression models, and classification techniques for data analysis
    • Learn and use the various association rules with the Apriori algorithm
    • Learn and use clustering methods including k-means, DBSCAN, and hierarchical clustering

  • What are the job roles available after getting an R certification?

    After obtaining an R certification, you can seek job roles in the form of:

    • R programmer
    • Data Scientist
    • Data Analyst
    • Data Architect
    • Data Visualization Analyst
    • Geo Statistician
    • Database Administrator
    • Quantitative Analyst

  • What does an R Programmer do?

    The primary responsibility of an R programmer is to use the R programming language for developing scripts that can be used for data manipulation, modeling, prediction, visualization, and reporting. By attaining an R certification, you will better understand the roles and responsibilities of R programmers.

  • What skills should an R Programmer know?

    An R programmer should be skilled at:

    • Statistics
    • Machine learning
    • Programming languages in addition to R
    • Visualization
    • Communication

    With this Data Science with R certification, you will be able to acquire these skills and learn much more about R programming and have a flourishing career ahead of you.

  • What industries use R Programming most?

    Industries that use R programming the most are academic, healthcare, consulting, government, insurance, finance, manufacturing, electronics, and technology-based industries. After seeking an R course, you can easily seek job opportunities in these top industries.

  • Which companies hire R Programmers?

    Some of the top companies hiring professionals with R certification are Facebook, Google, American Express, HP, Infosys, IBM, Deloitte, Capgemini, Oracle, Twitter, and Uber.

  • What book do you suggest reading for R Programming?

    While pursuing an R course, you can consider referring to the following top books for more detailed knowledge:

    • An Introduction to Statistical Learning: with Applications in R by Springer
    • R for Data Science: Import, Tidy, Transform, Visualize, and Model Data by Hadley Wickham
    • Discovering Statistics Using R by Andy Field R
    • For Dummies by Andrie de Vries, Joris Meys
    • The Art of R Programming: A Tour of Statistical Software Design by Norman Matloff

  • What is the pay scale of R Programmers across the world?

    By seeking an R certification, professionals can earn an average salary of $96,481 in a year

Data Science with R Programming Training in Bangalore

Bangalore's population is expected to reach 12 million (1.2 crore) by 2020. According to the 2011 census, Bangalore's population is 8.4 million, with a city area of 709 square kilometres. Bangalore, often spelled Bengaluru, is the capital of the Indian state of Karnataka. With a population of over 10 million people, it is India's third most populous city and fifth most populous urban agglomeration. Karnataka is one of India's fastest-growing states, with a projected GSDP growth of 8.2% in the 2010–11 fiscal year. During the 2019 financial year, Bengaluru. The per capita income in the region was around 230 thousand Indian rupees. 

The climate of Bangalore is a tropical savanna, with distinct wet and dry seasons. Bangalore has a more temperate climate throughout the year due to its high elevation, yet occasional heat waves can make summer miserable. Bengaluru's economy contributes more than 87 percent to the state's GDP, and it accounts for 98 percent of the state's software exports. The expansion of Information Technology (IT) in India has been fueled by the establishment and success of high-tech companies in Bangalore.

Top attractions in Bangalore are ISKCON Temple Bangalore, Cubbon Park, Wonderla Amusement Park, Lalbagh Botanical Garden, UB City, Visvesvaraya are some of the attractive places in Bangalore.

Our Bangalore Correspondence / Mailing address

Simplilearn's Data Science with R Programming Training in Bangalore

1st & 2nd Floor, IBIS Hotels Block Hosur Road Bommanahalli Bengaluru, Karnataka 560068

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