Overview

Business Analytics is now a mainstream technique in the hands of senior management to take business decisions. This course is targeted towards equipping mid and senior managers with the knowledge and skill to identify the opportunity of using data science and artificial intelligence for business benefit and leverage them for managerial decision-making. This course is not targeted at preparing participants for commencing a career in data science or artificial intelligence. Hence the course is light in coding and emphasizes on understanding, using, and interpreting data in organizations. At the end of this programme, participants will be able to

  • Identify areas in their organization where business analytics can be gainfully applied
  • Have a managerial understanding of the techniques and tools used in analytics, data science and AI
  • Develop skills and knowledge for effectively managing data science and analytics teams
  • Help build a data driven organization and a analytics team for the organization
  • Evaluate investment decisions for analytics projects in their organizations
  • The Course is NOT intended to equip the participants to become a data science professional.
Syllabus

Module 1: Analytics as Strategic Lever

  • Data and data literacy in organizations
  • Types of analytics – descriptive, predictive and prescriptive
  • Use cases of Analytics – An introduction
  • Good and bad Analytics
  • Deriving organization’s data science objectives from strategic business objectives
  • Building hypothesis for organizational decision making: use cases from different verticals
  • Limitation of analytics – where intuition still wins!
  • Case Study: Harvard article on “Data Science and Art of Persuasion”

Approximate duration = 6 hours (4 sessions)

Module 2: Revisiting Statistics for Managers

  • Describing and presenting data
  • Applying measures of central tendency in business metrics
  • Probability and its application in business
  • Sampling theories and their application in business
  • Hypothesis testing, use cases in business
  • Analysis of variance, use cases in business
  • Correlation and regression, use cases in business

Approximate duration – 15 hours (10 Sessions)

Module 3: Decision making using Algorithms & Machine Learning

  • Principal types of algorithms
  • Application of Bivariate and Multiple linear regression models
  • Classification algorithms – concept and use cases
  • Clustering algorithms – concept and use cases
  • Design of recommendation system

Approximate duration = 15 hours (10 Sessions)

Module 4: Spreadsheet Modeling for Business Decision

  • Modeling approach to decision making
  • Linear Programming approach to solve business problem, e.g.
  • Make-Buy decision
  • Investment decision
  • Blending problem
  • Production and inventory planning problem
  • Multi-period cash flow problem
  • Sensitivity Analysis and Simplex Method

Approximate duration = 6 hours (4 Sessions)

Module 5: Data Warehousing & Technology 

  • Data management and querying
  • Data extraction, transformation and loading (ETL) techniques
  • Fundamentals of data warehouse
  • Overview of technology stack to support analytics

Approximate duration = 3 hours (2 Sessions)

Module 6: Digital Media Analytics 

  • Scope and benefits of digital media analytics
  • Types of digital media analytics
  • Consumer insights using web and mobile app analytics
  • Social media analytics
  • Overview Text mining and sentiment analysis
  • Online reputation management

Approximate duration = 9 hours (6 Sessions)

Module 7: Big Data

  • Understanding Big Data
  • Understanding application of Big Data
  • Big Data application tools – Hadoop, MapReduce
  • Exploiting Big Data for business decision
  • Example from Facebook & Goggle

Approximate duration = 6 hours (4 Sessions)

Module 8: Application of Deep Learning and Reinforcement Learning in Managerial Decision making

  • Fundamentals of Deep Learning
  • Deep, Convolution and Recurrent Neural Network – concept
  • Use cases of Deep Learning in different industry verticals
  • Fundaments of Reinforcement Learning
  • Use cases of Reinforcement Learning in industry

Approximate duration = 6 hours (4 Sessions)

Module 9: Data Visualization and Story-telling

  • The art of story-telling with data
  • Data visualization – concept and application
  • Using self service data visualization tools (e.g. Tableau) to generate management reports and dashboards
  • Visualizing data using infographics
  • Evaluating an Analytics report

Approximate duration = 9 hours (6 Sessions)

Module 10: Managing a Large-Scale Data Science project

  • Data Science project management methods and governance
  • Application of Agile
  • Managing organizational change
  • Developing and managing a data science project contract

Approximate duration = 3 hours (2 Sessions)

Module 11: Developing a Business Case for Analytics Project

  • When is investment in data science justified and when not?
  • Identifying and quantifying benefits of a data science for an organization
  • Estimating investments in a data science project
  • Estimating return on investment in a data science project

Approximate duration = 3 hours (2 Sessions)

Module 12: Building a Data Driven Organization

  • New organization roles and governance for a data driven organization
  • Recruiting and retaining data science talent pool
  • Scaling a data team
  • Vendor eco-system for data science services

Approximate duration = 3 hours (2 Sessions)

Module 13: Data Privacy and Trust

  • Ethical Concern on data privacy and trust in Analytics
  • Methods to preserve privacy of sensitive data
  • Legal issues on data privacy
  • Recent case studies

Approximate duration = 3 hours (2 Sessions)

Module 14: Capstone Project The participants will be asked to work on a Capstone Project for a industry domain of their preference. It is expected that the participants will work on live data set from their own organization.

Eligibility

Graduates in any

discipline with minimum

-4 years of work experience

Placements
Campus
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Course Info

Fees: – 1,52,500/-
Duration: 7 Months
Study Mode: Online
Approved By: AICTE

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