Business Data Analytics

Program

Certificate in Business Analytics is designed to help participants master their business knowledge, the methods and the analytical tools to convert data into insights in marketing, finance and operations. In a connected world, data provide companies with the opportunity to align their marketing, finance and operations strategy with objective facts and figures. Participants will learn how to become data-driven managers, and will be able to spot analytical opportunities in a given business context.

Today, data is everywhere. We create it simply with the touch of a button. But how much of it is actually useful? Whether you are in finance, operations, sales & marketing or planning, you may be in touch with million data points every day without being aware of how to derive valuable information from this data. With BIL’s Business Analytics Program, you will be able to extract useful information from millions of bytes within minutes. It makes extensive use of data, statistical and quantitative analysis, explanatory and predictive modelling and fact-based management to drive decision making.

Detailed description of the assessment requirements.

  • Examination: 50%. Must be passed for an overall pass. 3 hour exam which covers all the unit content and includes multiple choice, essays and short answer questions
  • Major Project: 25%. This is an essay of 2,000 minimum words requiring understanding of one or more theoretical concepts covered.
  • Case Study: 15%. Students must apply their theoretical knowledge to a detailed case study

  • Presentation: 10%. Students in pairs provide a 15 minute presentation on a topic covered to demonstrate their mastery of the content and effective presentation skills

    The course content is divided into 4 modules as below
    Module 1:
    Unit Title Introduction to Business Analytics
    Learning Outcomes
  • Describe analytics
  • Apply the implications analytics and scope
  • Describe different theories applicable
  • Demonstrate decisions based on analytics
  • Summary of content / topics Content of the program covers the following:
  • Introduction to analytics
  • Analytics Definition
  • Business Analytics
  • Challenges and domains within analytics
  • Applications and steps of Analytics
  • Description of delivery strategy Delivery Strategies are:
  • Class room training sessions by Industry practitioners,
  • Application based work book exercises and
  • Assignments as do - it – yourself projects
  • Module 2:
    Unit Title R programming
    Learning Outcomes
  • Describe R and its applications
  • Apply the Data using R
  • Describe different theories applicable
  • Interpret data using R
  • Summary of content / topics Content of the program covers the following:
  • Introduction to R programming
  • Programming in R
  • Introduction to Statistics in R
  • Importing Data in R
  • Data Manipulation in R
  • Data Visualization in R
  • Description of delivery strategy Delivery Strategies are:
  • Class room training sessions by Industry practitioners,
  • Application based work book exercises and
  • Assignments as do - it – yourself projects
  • Module 3:
    Unit Title Data Exploration & Mining
    Learning Outcomes
  • Describe & apply Data Exploration and Mining
  • Describe different theories applicable
  • Interpret data using Data Exploration and Mining
  • Use various paradigms of Machine Learning
  • Summary of content / topics Content of the program covers the following:
  • Data Exploration and Preparation
  • Data Mining and Machine Learning
  • Description of delivery strategy Delivery Strategies are:
  • Class room training sessions by Industry practitioners,
  • Application based work book exercises and
  • Assignments as do - it – yourself projects
  • Module 4:
    Unit Title Statistics and Econometrics
    Learning Outcomes
  • Describe various statistical models
  • Demonstrate the implications of each model
  • Apply the different theories applicable in statistics
  • Make decisions based on statistical information
  • Summary of content / topics Content of the program covers the following:
  • Probability Basics
  • Expectation and Variance
  • Typical values of a random variable, quantiles
  • Conditional probability and Independence
  • Discrete distributions (Binomial)
  • Discrete distributions (Poisson)
  • Discrete distributions (geometric)
  • Behaviour of large sample (Law of Large Numbers)
  • Central Limit Theorem, Normal Distribution
           (2 sessions)
  • Covariance and correlation (2 sessions)
  • Point Estimation of the mean and the variance
  • Internal Estimation
  • T, F and chi2 distributions (2 sessions)
  • Maximum likelihood Estimation
  • Linear Regression
  • Description of delivery strategy Delivery Strategies are:
  • Class room training sessions by Industry practitioners,
  • Application based work book exercises and
  • Assignments as do - it – yourself projects
  • 8 Full days ( Weekends )
    10.00 am. to 6.00 pm

    25,300/- + Applicable Taxes

    For further details regarding contents,
    E-mail: training@bseindia.com