R - Course and Certification

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5 Weeks
9:00 AM- 1:00 PM

This course is open for Enrollment and Payment.

In case you want to Register now and take up this course later, you can register by clicking on " Register" section.

If you have any query, you can call/mail or send your query by clicking on " Send a Query" section.

About the Course

Analytics is the new age career option and there are immense opportunities in this space. There are various tools available to carry out Analytics activities. Two tools which stand out are SAS and R. SAS is a proprietary software with a huge cost attached to it, while R is an open source tool which can be downloaded and used freely for unlimited use.

R is gaining more popularity these days, first because of its open source & low cost nature, and second because of the fact that big data tools like Hadoop are open source too and integration between these and other open source tools are seamless. And many a time the Analytics tasks are ad-hoc and do not require a commercial tool. This is adding to the popularity of R tool.

This course provides an in-depth knowledge of R and practical exposure as well to run various Analytics techniques on it. In this course we cover basics of Analytics also so that you become aware of theoretical aspects too.

Course Objective

After completion of this course, you will be able to:

  1. Learn basic Probability & Statistics.
  2. Learn Machine Learning techniques - Classification, Association and Cluster Analysis.
  3. Learn R in Detail.
  4. Learn how to carry out following tasks in R - Data visualization, Probability distribution, Linear regression, Logistic Regression, Naive Bayes Model, Decision Tree, KNN-K Nearest Neighborhood, Support Vector Machine.
  5. Learn why Deducer is important for R. Learn in detail about Deducer.
  6. Learn about R packages like RCurl, rjsonio,lubridate,stringr,plyr,Hmisc,tm,wordcloud,twitteR
  7. Work on a live project where you need to extract live social media data and do analysis on that using R.

Why is it the right course for you?

If you want to get knowledge of Analytics and learn practical knowledge of it by using it on Analytics tool such as R then this is the right course for you.


You should be aware of basic mathematics.

Course Curriculum

Section A: Introduction

1. Analytics Introduction

What is Analytics?, Popular Tools, Role of a Data Scientist, Probability , Statistics, Machine Learning and Big Data. Parametric, Non-Parametric Statistics and Time Series analysis.

2. R Introduction

Introduction to R, How to download and install R?, R GUI, R Packages, How to access functions in package, Data types in R, R as a calculator, Data import methods for different format.

3. What is the difference between Business Intelligence, Data Warehousing, Analytics and Big Data

In this module you will get a clear idea about the distinctions between BI, Data Warehousing, Analytics and Big Data and learn how these Data Science technologies co-exists together.

4. Framework of Business Intelligence and Data Science Study

In this module you will learn about various discipline of data sciences and how are they interlinked together. You will also learn about various learning and job related opportunities and how can you transition yourself for next generation roles.

Section B: Analytics

After completion of this module, you will be able to:

  1. Learn basic Probability & Statistics.
  2. Learn Machine Learning techniques - Classification, Association and Cluster Analysis.
  3. Learn Classification techniques like Decision Tree Classifier, Rule based classifier, Instance based classifier, Nearest neighbor classifier, Naive Bayes Classifier,Artificial Neural Networks, Support Vector Machine and Ensemble Methods.
  4. Learn Association techniques like Rule Mining, Naive Algorithm, Apriori Algorithm.
  5. Learn Cluster techniques like Computing Distance, Partition Methods (K-Means Method), Hierarchical Methods, Agglomerative method, Divisive Hierarchical method, Density based methods.

Section C: R in Detail

  1. Data visualization with R
    • Creating a graph
    • Adding rug to plots/graphs
    • Saving graphs
    • Viewing several graphs
    • Kernel density plots
    • Compare groups via kernel density
    • Dot plots
    • Bar plots
    • Stacked bar plot
    • Grouped bar plot
    • Line chart
    • Pie chart
    • Pie chart with annotated percentages
    • 3d pie chart
    • Creating annotated pie chart from data frame
    • Box plot
    • Violin plots
    • Simple Scatter plots
    • High density scatter plots
    • 3d Scatter plots
    • Heat map
    • Basic Statistics with R

  2. Probability distribution with R
    • Binomial distribution
    • Poisson distribution
    • Continuous uniform distribution
    • Exponential distribution
    • Normal distribution
    • Simple linear regression
    • Estimated simple regression equation
    • Qualitative data
    • Frequency distribution of qualitative data
    • Relative frequency distribution of qualitative data
    • Quantitative data
    • Histogram
    • Scatter plot
    • T-test
    • Linear regression

  3. Linear regression with R
    • How to Find the Regression Equation
    • How to Use the Regression Equation
    • How to Find the Coefficient of Determination
    • How to calculate coefficient of regression using R
    • Calculation of error in linear regression
    • How to calculate standard error in linear regression using R

  4. Logistic Regression with R
    • Modeling Dichotomous Outcome Variables
    • The Logistic Regression Model

  5. Regression with regularization
    • Regularization in statistics and machine learning

  6. Naive Bayes Model with R
    • Installing and Running the Naive Bayes Classifier

  7. Decision Tree with R
    • Rpart (decision tree implementation in R)
    • Grow the Tree

  8. KNN-K Nearest Neighborhood
  9. Support Vector Machine
    • Available Implementations in R

  10. Deducer
    • What is Deducer
    • How to download Deducer?
    • Install Deducer with R
    • Deducer Interface
    • Deducer Workspace
    • Deducer Plugins
    • Data view
    • Variable view
    • Data menu
    • Sorting
    • Subsets
    • Transforming data
    • Analysis menu
    • Packages and data

  11. R Packages
    • RCurl
    • rjsonio
    • lubridate
    • stringr
    • plyr
    • Hmisc
    • tm
    • wordcloud
    • twitteR

Section D: Project

Sentiment Analysis Using R

In this project, following tasks will be performed:

  1. Download raw data from Twitter using twitter APIs.
  2. Connect R to twitter using twitteR package.
  3. Download twitter data on R platform and analyze it there.
  4. Specify positive sentiments words and negative sentiments words and prepare a reference file of these.
  5. Compare twitter data with reference files and find out the percentage of positive versus negative tweets.
  6. Analyze the data and prepare a sentiment analysis for multiple brands.

Project Assessment

Project assessment will be done by the Trainer and a grade will awarded based on the performance on project. Grading will be done on the scale of 1 to 5, 5 being the outstanding performance and 1 being the Unsatisfactory performance. Scale is as below:

  1. Outstanding
  2. Very Good
  3. Good
  4. Average
  5. Unsatisfactory

Course Duration

Online Classes : 20 Hours

There will be seven instructor led interactive online classes during the course. Each class will be of approximately four hours. If you miss a class then you can reschedule it in a different batch or you can also access Class video recordings anytime.

Project Work : 25 Hours

Assignment work will be given to learners to be completed during the course duration.

Course Work : 40 Hours

Study material of 40 hours or more will be given as a course work to be completed.

Exam : 1 Hour

A proctored exam of 1 hour will be conducted for final assessment.

Course Features

  • Live Classes

    Live Instructor Led classes from Industry Experts. Option to choose from Online or Classroom Lectures. Case studies from real life projects.

  • Ongoing Research

    Research team works hard to bring out the latest innovations and best practices of course subjects. Courses are evolving continuously; they never get stale.

  • Be More Productive

    Get work related tips and perform your work more efficiently. Once you know the tricks of trade, you become more productive.

  • Industry Experts

    Classes are conducted by Industry Experts. Learners gain from world class curriculum and extensive experiences of Trainers as well.

  • Easy Reschedule

    Have you missed a class? Don't worry !!, You can watch the class videos or you can also request for a reschedule. We will invite you for next class for Free.

  • Learning Material

    Learners get unlimited access to online and offline materials. Don't worry if you miss any class, we will be providing you a repeat class online or offline.

  • Learning Support

    Learners are encouraged to ask online and offline questions. Our team of Trainers makes it a priority to answer these questions.

  • Money-back Guarantee

    If you are not satisfied with the quality then take full refund within the seven days of first class. No questions will be asked.

  • Career Support

    Learner's resume is reviewed and a one-to-one discussion is arranged with an expert to advice on career roadmap and job opportunities. For details, visit Career Centre


Certificate of Participation

A certificate of participation will be awarded after participating in the training program. The name of certificate is "BIWHIZ CERTIFICATE OF PARTICIPATION ON R".

Certification after Completion

A certification will be issued after assessment of assignments, course work requirements, projects and a written test as per the course curriculum. After successfully completing all the requirements and passing the written test, a certification will be issued. The name of the certification is "BIWHIZ CERTIFICATION ON R".

Certificate Issuing Authority

BIWHIZ is part of the company "Business Intelligence Consultant and Services LLP". Certificates are issued by "Business Intelligence Consultant and Services LLP". This is a registered company with Ministry of Corporate Affairs, Government of India.

Sample Exam Questions

This sample is only for illustrative purpose and only basic level questions are displayed here. Actual exam questions may be completely different with different format as well. Please contact your coordinator to know more about prevailing exam format.

What is the value of z ?

x <- a(3,5,2), y <- a(5,1,2), z <- x*y

  1. (15,5,2)
  2. (15,5,4)
  3. (3,5,2)
  4. (15,1,4)

What is the value of z ?

x <- a(1,-2,2), y <- a(2,4), z <- x*y

  1. (2,-2,4)
  2. (2,-8,2)
  3. (2,-8,0)
  4. Syntax error

Which is not a sort in R?

Choose one.

  1. Bubble
  2. Quick
  3. Fast
  4. Merge

Which is a package?

Choose one.

  1. twitteR
  2. FacebookR
  3. LinkedinR
  4. SocialMR

Why Deducer is used?

Choose one.

  1. GUI
  2. Performance
  3. Extra functions
  4. APIs

Which is not a data structure in R?

Choose one.

  1. Vector
  2. List
  3. Matrix
  4. Box plot

Frequently Asked Questions

  1. Is it necessary to have any prior knowledge of Probability & Statistics before starting this course?

    It's good to have knowledge of basic mathematics and good to have school level of mathematics and probability knowledge however you will be provided sufficient coaching and material to learn these concepts from scratch.

  2. Is this course for me? What value would it add to my career?

    If you are planning to get a practical exposure of how Analytics techniques are performed then this is the right course. This course will give an extra advantage if you are planning to enter into Analytics.

  3. I guess I need to have very fast Internet connection to be able to attend these courses?

    Generally 1 MB connection is sufficient however lower bandwidth connections are also working fine.

  4. Can I request for another class if I miss it?

    You can watch the recorded session video or you can also attend the same class in next batch.

  5. Why Certification is included in the course?

    This is to make sure that a learner has understood the course content and BIWHIZ has verified the knowledge level of the Learner. Certification is the proof that you have achieved a certain level of expertise on course and any authorized organization can verify that with us.

  6. What if I am not able to clear the Certification exam in first attempt?

    You can take extra attempts for free.

  7. What is the learning support and would it be available after completing the course as well?

    You can raise your queries and doubts during and post training period. All queries will be resolved by R experts.

  8. Do you help in career related issues as well, like reviewing resume, mentoring for my career growth?

    Yes, we have a panel of R experts who will guide and mentor you; please check Career Centre for more details.

  9. Will you sell my data to Recruitment/marketing companies or will you use it for Recruitment or any other activities not related with Training?

    NO, Never. Your details are highly confidential and safe with us. But If you are willing to accept any such calls then you can inform us in advance with a specific need and we will contact only for those specific requirements. For a detailed privacy policy please check Terms, Conditions & Privacy Policy.

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