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XLRI | Postgraduate Certificate in Business Analytics

1 Year / Live & Interactive / Weekend Classes / Batch 5

Course Snapshot
  • FeeINR 3,00,000 + GST (To be Paid in Installments)
  • Work Experience1 - 30 Years
  • Duration1 Year
  • Delivery MethodOnline
Course Detail

Program Overview
XLRI's Post Graduate Certificate in Business Analytics is a 1-year course which provides the perfect base for professionals to master the art of analytics. The course focuses on providing an in-depth knowledge of business analysis techniques and frameworks and their application in business decisions. The scope of business analytics can be broken into three main areas; Descriptive analytics, Predictive analytics and Prescriptive analytics. In a nutshell, it is the simultaneous application of statistics, computer programming and operations research to achieve the required outcome.
This course is specifically designed to:
● Help analytics professionals gain in-depth knowledge in various areas of analytics and gain managerial insights through data analysis
● Transform analytics professionals into exceptional, cross-functional leaders who integrate all disciplines to achieve the organisation's strategic goals with the help of advanced analytics
● Help face challenges and complexities in analytics field, thereby equipping those working in analytics field with the necessary skill-sets to adopt an appropriate course of action

Who Should attend?
● Working Professionals employed in the areas of Big Data, IT Services, Marketing, eCommerce, Research etc. who want to learn contemporary, critical and implementable aspects of business analytics
● Business Analysts who would like to gain in-depth knowledge of concepts, tools and techniques related to data management and analysis
● Functional Managers, Business Leaders and Project Managers responsible for handling large and complex databases with a need to excel in function specific analytics
● Working executives with analytical aptitude who have little or no formal education in Business Analytics, but now feel the need to embrace technologies which will help them generate insights from data
● Working Professionals who are in the early stages of a career in business analytics and seeking to upgrade their skills and knowledge

Desired Candidate Profile

● For Indian Participants – Bachelors in Engineering (10+2+4) or Graduates in Computers, Science, Commerce or Business (10+2+3) from a recognized university (UGC/AICTE/DEC/AIU/State Government)
● For International Participants – Graduation or equivalent degree from any recognized University or Institution in their respective country
● Mathematics or Statistics as a subject in Class XII or Graduation with at least 50% marks
Formal education in and knowledge of at least 1 programming language
● This course 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 Python and R (laptop/desktop)
Enrolment Criteria
● Participant selection into the programme is based on an elaborate selection process including validation of academic performance and work experience and submission of a Statement of Purpose (SOP)
Minimum 1 year of work experience as on 01 Jul 2021

Course Modules

Tools of Business Analytics
● Introduction to R
● Introduction to Python
● Spreadsheet Modelling & Power BI
● Data Visualization and Descriptive Statistics
● Various graphs, charts and basic statistical techniques including data properties
Statistics for Data Science
● Hypothesis Testing
● Discriminant Analysis
● Factor Analysis
● Principal Component Analysis etc.
Regression Techniques
● Linear Regression Model
● Discrete Choice Models
● Logistic Regression
● Multinomial Logistic Regression
● Probit Regression
Data Mining
● Data Analytics Life Cycle
● Anomaly Detection
● Association Rule Learning (Dependency Modelling)
● Clustering/Classification/Regression/Summarization
● Meta Analytics
Machine Learning
● Neural Networks
● Multilayer Perceptron (MLP)
● Support Vector Machines (SVM)
● Nearest Neighbour Algorithms (KNN)
● Introduction to Artificial intelligence and Deep learning
Text Mining
● Information Retrieval
● Lexical Analysis
● Pattern Recognition
● Tagging
● Annotation
● Information Extraction
● Natural Language Processing (NLP)
Analytics Applications (Covering a range of applications in the following domains)
● Marketing
● Finance
● HR
● Operations
● Supply Chain Management
● Digital Media Analytics
Prescriptive Analytics using Optimization and Simulation
● LP Simplex
● GRG and Evolutionary using Excel Solver
● Simulation
Business Forecasting
● Demand Management and Forecasting
● Applications of Time Series Models [ARIMA, ARCH, GARCH] etc.
Big Data Analytics
● Data Management in Big Data Era
● Concept of Hadoop
● Data Stream Analytics
● Recommender System etc.
3-Month Capstone Project