Data Science Series – Level IV

Training in Big Data Analytics & Data Visualization with R programming

Course Objective

Hands on program for learning programming in R-Statistical and Data Science programming language for big data analytics techniques & advanced Data Visualisation.You will learn to use R for very fast, easy and efficient data mining, cleaning, analysis and advanced visualization on large data sets.

Suitable For

For executives and researchers engaged in and/or interested to work on large data sets quickly using advanced analytics as well as Visualization techniques for faster, easier and better Interpretation and Reporting across different functionalities.Starting step for those pursuing Data Science, Machine Learning, AI.

Ambeone’s Certification Training in “Big Data Analytics & Visualization using R programming”

R is a powerful language for statistical modeling, data mining, data manipulation & exploration. Also, it is one the most advanced language for data visualization.

R is suitable for Non-IT Managers who do not want to get into too much coding and programming and want to focus on data analysis, data mining & data visualization.

In other words, R is today’s excel and much more!

Hence it is an essential step for those interested in the field of Data Analytics and Data Science  to train in Programming with R for Advanced Analytics & Visualization in Dubai.

The program provides you expertise in Quick & High-End Analytics & modeling and is the starting step for learning Machine Learning & Artificial Intelligence.

R and Python are two key languages in the Big Data Analytics & Visualization in Data Science Domain and are critical component for developing expertise in  Machine Learning and Artificial Intelligence.

Learning to program with R or Python or both for Big Data Analytics have their own advantages and usage and we believe that mastering them gives a strong hold for developing a career as a Data Scientist.

We offer the above module with Python programming as well.

This course can also be taken in conjunction with professionals management programs like Market Research, Marketing Strategy,HR Analytics, Data Driven Decision Making , Negotiation Skills , Supply Chain Logistics etc. to ensure the advanced analytics and visualization skills are used to enhance the  subject domain expertise with efficient and effective use of data.

Topics Covered in our certification Training in Programming with R for Big Data Analytics & Visualization

  • Basics of Data Analytics (Level I)
  • Basics –  Vectors, Matrices, Factors, Data Frames, etc.
  • Relational Operators, Equalities, Logical Operators
  • Conditional & Control – If Statements, Loops, Writing Functions
  • The Apply Family of Functions
  • DPLYR Package – Grammar of Data Manipulation
  • The Pipe Operator, Group_by & Summarize Operators
  • GGPLOT2 & GGVIS packages for data visualization
  • PLOTLY Package for interactive data visualization
  • R-Shiny – Making customized interactive BI Dashboards
  • Cleaning Data with Tidyverse, reshape3, stringR, etc.
  • Connecting with SAS, SPSS, SQL Databases, etc.
  • Other Important Packages & Programming Concepts.

Our carefully planned and recommended learning structure for Data Science Series

LevelCourse NameKnow More
Level IFundamental of Data Analytics & Interpretation ,Simple Measures of Data Click here
Level IIBusiness Analytics with KPI Measurement using StatisticsClick here
Level IIIStatistics for Data Analytics & Data ScienceClick here
Level IVBig Data Analytics &  Visualization with R Click here
Level VAdvanced Data Mining & Manipulation with Python Click here
Level VIPredictive Modeling & Evaluation with Machine Learning Click here
Level VIIAdvance Machine Learning and Artificial Intelligence with R & PythonClick here
Level VIIIApplied Analytics-Using Data Science & Machine Learning in Business AnalyticsClick here
Level IXNeural Network & Unsupervised Learning for Advanced AIClick here

Course Duration

32 hours of Instructor Led Sessions


40-50 hours of Assignments & Projects

Course Format

5 days intensive Bootcamps/Workshops for Corporate batches


Weekend Sessions for Public batches

Course Pre-requisite

There are no pre-requisites for this course.

However it will be beneficial if the participants have some business and analysis experience in order to understand applications of R for statistical techniques in business environments.

In addition, it is advisable for participants to complete our course on Foundation in Statistics, if they wish to  pursue Data Science domain.

Course Schedule for Training in Programming with R for Big Data Analytics & Visualization

Course Course FormatStart Date DurationRegister
Programming in PythonWeekend Afternoon2nd June 20246 WeeksRegister Here
Big Data Analytics with RWeekend Afternoon 18th June 20246 WeeksRegister Here
Programming in PythonWeekend Afternoon23rd June 20246 WeeksRegister Here

Course Details

  • Duration of the course is 32 hours of Instructor Led Class Room code-along Training with 40 hours of self/group study with assignments  Hours.
  • Students have to submit a Capstone project using R programming for Advanced Analytics & Visualization.
  • This course is offered as,
    • 5 Day Intensive Boot-Camp.
    • Evening Classes. Two 2-hour sessions a week for Eight weeks in the evenings.
    • Once a week, Four Hours Classes during Weekends for Eight Weeks
    • As part of our ‘Advance Program in Data Science and AI’
  • We currently offer this course Dubai, Abu Dhabi, Delhi, Mumbai, Bangalore and Nigeria.
  • Checkout our course schedule more information.
  • Participants must bring their own laptop. Preferably with more than 8GB ram.
  • This course will be taught using  R as the programming language.
  • All softwares and Databases used for the course are open-source and participants will be taught how to install and set-up the environment.
  • All training topics covered in the course will be taught using relevant industry specific case studies and examples.
  • This training course is very hands-on/practical and is not a lecture or seminar. Participants will be expected to complete exercises and case studies on their own with necessary support and guidance from the instructor.



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