This Post Graduate Program in Business Analytics is a career centric course which is designed in consultation with industry veterans. This unique program prepares you to become a Data Manager as you will become an expert in data science and business management techniques.

• Duration: 6-12 months
• Learning Mode: Faculty-led online
• Eligibility: BE, BTech, BSc / MSc (Statistics), MBA
• 68,000

Big Data 101

• Volume
• Variety
• Velocity
• Veracity
• Valence
• Value

Data Relationships and Data Model

• One-to-one relationship
• One-to-many relationship
• Many-to-many relationship
• Flat model
• Hierarchical model
• Network model
• Relational model
• Star schema model
• Data vault model

Clustering Algorithms

• partitioning
• hierarchical
• grid based
• density based
• model based

Clustering Algorithms – UPGMA, single Link Clustering

• Define the pain point
• Define the goal
• Identify the actors
• Identify the impacts
• Identify the deliverables

Mathematics Modelling

Introduction to key mathematical concepts

• eigenvalues and eigenvectors

Application of eigenvalues and eigenvectors

• investigate prototypical problems of ranking big data

Application of the graph Laplacian

• investigate prototypical problems of clustering big data

Application of PCA and SVD

• investigate prototypical problems of big data compression

Making Data Sets

R Programming

Text Analytics

Basics of text analysis processes

• Annotators
• analysis results
• feature structure
• type
• type system
• annotation
• common analysis structure
• Web crawling

Statistics 101

Python

Dictionary and Tuples

Statistics with R

Introduction to Data

• Data Basics
• Overview of data collection principles
• Experiments - Principles of experiment design
• Examining Numerical and Categorical data
• Comparing numerical data across groups

Introduction to Probability

• Introduction
• Conditional probability
• Bayes’ Rule

Distributions

• Discrete Distributions
• Continuous Distributions

Introduction to linear regression

• Correlation
• Line fitting
• Fitted values
• Residuals
• Basic introduction to multiple regression

Foundations for inference and estimation

• Variability in estimates
• Sampling distribution
• Confidence intervals
• Margin of error and ascertaining a sample size

Foundations for inference and hypothesis testing

• Nearly normal population with known SD
• Hypothesis testing framework
• Two Tailed and One Tailed tests
• Testing hypothesis using confidence intervals and Critical Z values
• One-sample means with the t distribution with unknown population SD
• Inference for a single proportion
• Decision errors (Type 1 and 2)
• Hypothesis testing using p-values
• Choosing a significance level
• Power and the type 2 error rate

Linear Regression and Multiple Regression

• Introduction to F-statistic
• Hypothesis Tests
• Intervals
• Coefficient of Multiple Determination
• Interpreting the model output
Data Mining 1 - Machine Learning with R & Python

Forecasting

Data Visualization with Tableau

Need for visualizing data

• Same dataset, different interpretation
• Read texts well, not numbers
• Brain processes visuals by short circuiting brain’s pathways
• Quicker conclusions | Speed

Research methodologies

• Problem Formulation
• Literature review
• Methodology
• Analysis
• Finding and Interpretation
• Suggestion
• Conclusion
• Bibliography

Importance of Big data visualization

• Big Data Visualization

Case study discussion

• HR – Case Study with Data

Geomapping in Tableau

• Create a geographic hierarchy
• Build a basic map
• Change from points to polygons

Qlik view – Basics

• Creating a simple Google Chart with in data
• Image generation, Line, bar, and pie charts.
• Scatter plot
• Specification of attributes

• Using Google Docs as database to store graphical data
• Specifying the range of data and selecting columns

Web Analytics

Display Marketing

RDBMS with SQL and DWH

Mentors

Has spent two decades in the corporate world in areas as diverse as Cryogenics, Steel, International Trade, Consulting and IT with organizations such as British Oxygen, Tata Steel, PwC and Compaq-HP. He has taught at the University of Iowa and has been a visiting faculty at IIM Lucknow, IIM Raipur, IIM Udaipur, IIM Shillong.

Charanpreet Singh

BTech (IIT Kanpur), MBA (University of Iowa), Co-Founder and Associate Dean - PRAXIS

He has worked as an online SAS trainer at Wireclass and provided online analytics training in U.S.A. and U.K. He worked as a Professor of Data Mining, Data Visualization and Advanced Analytics at iNurture Education Solutions Pvt. Ltd after which he has joined Praxis Business School as an Assistant Professor of Business Analytics.

Gourab Nath

MSC (WB State University)

Comes with an experience of 27 years delivering Management and IT consulting services in large organizations like (PwC) and CMC Ltd. He was a partner in the Management Consultancy Business at PwC and led large software projects in India and abroad.

Jaydeep Mukherjee

BTech (IIT Kharagpur), MTech (ISI Kolkata)

Suresh Krishnaswamy (popularly known as Sky) heads our Big Data & Business Analytics Center of Excellence. Sky has rich experience of over 26 years ranging from IT consulting, transition, transformation,applications development, to strategy making and business analyses with leading global IT and Consulting services companies in India and abroad.

Suresh Krishnaswamy

Head - COE - Big Data and Analytics

Has close to 2 decades of industry and 5 years of teaching experience. Has worked as Senior Scientist at TCS Innovation Labs after stints with Akamai Technologies, ONGC and Hindustan Motors. His areas of interest include Advanced Statistical Modeling, Data Mining, Graph Theory, Discrete Math and Internet Technologies.

Jaydip Sen

B.E (Jadavpur University), M.Tech(ISI, Kolkata); Pursuing PhD in Information Privacy in IoT

He is listed as one of the 10 prominent analytics academicians in India by Analytics India Magazine.Has spent nearly two decades in the IT, software and management consultancy business and has worked in Tata Steel, Tata IBM, PwC, where he was a partner and in IBM where he was the head of the Kolkata Delivery Centre.

Dr. Prithwis Mukerjee

B.Tech (IIT Kharagpur), M.S., Ph.D. (University of Texas at Dallas) Program Director - Business Analytics

Has been one of the most prominent market researchers of the country in the last decade and has worked in the top three multinational MR agencies of India - The Nielsen Company, TNS and IMRB International for 13 years in different functional and leadership roles. He was Associate Director at Nielsen and Group Business Director at IMRB International.

Prasenjit Das Purkayastha

M.Sc (J.U); PGDM (Goa Institute of Management)

Has worked in the industry for 4 years in Planning and Operations at HPCL prior to joining academics. He is actively involved in corporate training and has successfully completed training sessions on Data Mining processes in organizations like Abzooba, Infosys, TCG, ICICI Bank.

Demo of a live session

Praxis Business School, Kolkata, is a premier B-School whose courses are rated among India's top two in Big Data and Analytics domain. It is one of the most trusted and influential management education institutions in India. Praxis Business School is motivated by the desire to generate business professionals who can partake in and add to the economic development of the country.

Career Benefits

In the current landscape, Business Analytics Professionals are selling like hot pancakes on a winter day. They are in high demand due to their analytics and managerial skills. Their ability to convert meaningless data into insightful business solutions is an asset that is well acknowledged and heavily compensated by major companies today. The career options available to a trained Business Analytics Professional are as follows:

• Data Analyst
• Project Manager
• Program Manager
• Data Manager

Outcome of the Program

The new and exhaustive data science skill set acquired through this online, business analytics certification course would enable you to build your analytics career optimally. PGP in business analytics certification is one of the key requisites in any large organization. The time is at its best for someone to take up a career in this domain. Enormous opportunities and extreme dearth in getting candidates force large organizations go helter-skelter. It is imperative that career seekers grab this opportunity.

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