Short Duration Programme


Today every business is trying to engage with data science in one form or another. Unfortunately, very few businesses have been able to even grasp the idea of what constitutes data science, let alone a useful or profitable implementation of the same. The phrase - data science triggers thoughts on related terms like business analytics, operations research, business intelligence, competitive intelligence, data analysis and modeling, etc. In addition, the latest craze doing the rounds is big data analytics. No wonder an average business manager is utterly confused about how to start introducing data science in the organization. Meanwhile, popular press keeps exhorting managers not to be late in embracing data science. The consequence is that business managers employ technical solutions without having a good idea of how data science can actually add value to their businesses.
To preside over a successful implementation of data science in the organization the managers must have a good understanding of the basics, and it is quite impossible to get a feel of data science without getting one’s hands dirty. This course is an entirely hands-on approach to data science where participants would be working with data sets to generate insights for businesses. The tools that we will use are Excel and R.
The objective of this course is to introduce participants to the world of data science and who have not got a foothold into the techniques. The purpose of this course is to strip away all the distractions around data science – codes, tools, etc., and teach the techniques using practical cases that can be understood and appreciated by someone with an elementary knowledge of mathematics.

Who Should Attend

  • Professionals who want to learn practical aspects of data handling across applicable areas like Big Data, IT Services, Marketing, eCommerce, Research etc.
  • Project Managers, Business Managers and Senior Leaders who have the responsibility to manage large data analytics/big data based projects and would like to gain an understanding of this domain.
  • Young professionals and Managers who have little or no formal education in Business Analytics, but who now feel the need to embrace technologies which will help them generate insights from data.
  • Executives with analytical aptitude who are interested in and want to learn Data Analytics through hands on practice on popular tools.
  • This programme is entirely hands-on and so it is recommended, though not a necessity that students have two devices – one to follow the lecture, and the other for hands-on practice on Excel and R. However, it is mandatory that the sole or primary device must be a laptop or desktop to facilitate hands on practice on tools.


  • or Indian Participants - Graduates (10+2+3) or Diploma Holders (only 10+2+3) from a recognized university (UGC/AICTE/DEC/AIU/State Government) in any discipline.
  • For International Participants - Graduation or equivalent degree from any recognized University or Institution in their respective country.
  • For Indian and International Participants – Interns or Working professionals.

Programme Prerequisites

  • Mathematics as a subject up to Class XII
  • Working familiarity with MS Excel including ability to execute basic functions (e.g. min, max, count, average), formatting data, create graphs, insert charts etc. Familiarity with R is desirable but not mandatory.
  • Familiarity with R is desirable but not mandatory.
  • Knowledge of basic programming concepts will be beneficial.
  • This programme is entirely hands-on and so it is recommended, though not a necessity that students have two devices – one to follow the lecture, and the other for hands-on practice on Excel and R.


The classes for this programme will be held through LIVE lectures that will be beamed online via internet to student desktops/laptops or classrooms using Talentedge’s Direct To Device platform. The pedagogy will comprise of lectures, case studies, interactive sessions, project work and class exercises imparted by XLRI’s faculty in order to help participants gain the knowledge, understanding, and hands-on skills to immediately apply their learning in the workplace. Additionally, participants opting for Certificate of Completion will be assigned project work and an end course assessment that will be evaluated by the Faculty in addition to providing feedback.
All participants will also be granted 24X7 access to Talentedge’s Cloud Campus comprising of learning aids, study materials, reference materials, assessments, case studies and assignments etc. as per the requirement of the programme. Students can chat real time with the professors during the live class and also post all other programme related queries offline on the Cloud Campus.

Course Benefits

  • Opportunity to earn Certificate of Completion or Certificate of Participation from XLRI
  • Hands on exposure to popular Business Analytics tools like Excel and R.
  • Programme completely oriented towards imparting practical and working knowledge of tools.
  • Course content and structure designed entirely by XLRI
  • Lectures imparted by eminent faculty from XLRI.
  • Fully online program with LIVE interactive lectures that provides a “real” classroom experience in a “virtual” environment.
  • In the event that students miss the LIVE lecture, he/she can request “On Demand” access to the recorded session.
  • Seamless technology that can transmit lecture videos effectively at home broadband connection of 512 kbps.
  • User friendly and easy to use technology interface. No complicated hardware or software installations required.
  • Virtual classrooms that allow for active interactions with other fellow students and faculty
  • Convenient weekend schedules.
  • Students on our virtual social learning platform are provided access to course presentations, case studies and other learning aids and reference materials as applicable for specified courses.
  • Students can raise questions and doubts either real time during the live class or offline through the Cloud Campus.


A minimum of 70% attendance to the LIVE lectures is a prerequisite for the successful completion of this programme. There may be are periodic evaluations built in through the duration of the course. These maybe in the form of a quiz, assignment, project or other objective/subjective assessments as relevant and applicable to the programme. The evaluations are designed to ensure continuous student engagement with the course and encourage learning. Participants who successfully complete the same along with the requisite attendance criteria, an end course assessment and project work will be awarded a certificate of completion by XLRI. Participant who opt out of the evaluated exercises and meet the requisite attendance criteria will be awarded a certificate of participation by XLRI. No mark sheet or grade sheet will be provided to the participants.

Program Contents

Data Science Using Excel and R is organized in eight modules. The first part of the course will introduce participants to R and Excel. The second part will consist of solving real-life problems using data analytic techniques. The eight modules are:

  1. Introduction to Excel
    • Working with Pivot Tables
    • Working with Functions – VLOOKUP, MATCH, INDEX, OFFSET, INDIRECT, etc.
    • Array formulas
    • Solver
  2. Introduction to R
    • Basic Classes of R Objects
    • Working with Vectors, Matrices, Dataframes
    • Advanced functions in R
    • Looping in R
    • Writing functions in R
    • An introduction to data analytics in R
  3. Market Basket Analysis
    • Implementing Apriori algorithm in Excel and R
    • Calculating Lift
  4. Customer Segmentation: Cluster Analysis
    • K-means Clustering Using solver
    • Generating Insights from the Clusters
    • Implementing Spherical K-means Clustering Using Excel and R
  5. Optimization Modeling
    • Simple Linear Programming
    • Minimax Formulation
    • Modeling Risk within a Linear Program
    • Implementation of Optimization Models in Excel and R
  6. Classification Techniques
    • Naïve Bayesian Classifier
    • Learning Bayes Rule to Create an AI Model
  7. Regression
    • Training Linear Regression Models
    • Statistical Significance of Models
    • Evaluating Model Performance
    • Logistic Regression
    • Comparing Models with ROC curves
    • Implementing Models using Excel and R
  8. Forecasting
    • Simple Exponential Smoothing
    • Holt’s Trend Corrected Exponential Smoothing
    • Holt-Winter’s Method
    • Prediction Intervals Using Monte Carlo Simulation
    • Graphing Predictions Using Fan Cart
    • Implementing Models using Excel and R


Duration of the Course: 55-60 Hours covered across 18-20 weeks
Schedule of Classes: every Sunday (10:30 am to 01:30 pm IST)
Once in a month on Friday (07:00 to 10:00 pm IST)

Payment & Installment Schedule
  For Indian Participants
 Application Fee Rs. 30,000 + Tax
 Last Date: 2nd August 2017
 Installment I Rs. 15,000 + Tax
 On or Before: 2nd August 2017
 Installment II Rs. 25,000 + Tax
 On or Before: 10th October 2017
 Total Fee Rs. 70,000 + Tax

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