Post Graduate Program in Business Analytics

with Placement Assurance---Duration : 12 Months

Business Analytics with Placement

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Data Science with IIKMBA

Post Graduate Program in Business Analytics with Placement Assurance

Evolved and designed by veterans in the Analytics industry, this program prepares students and working professionals to establish a hi-flying globe-trotting career in the growing Data and Analytics domain. A perfect blend of technology, Data science and business cases and insights, the program stands out as among the best in the world. This is a career oriented program that covers all the key aspects of Data Analytics and Visualization. Best suited for Sales/Marketing/Statistics branches. A great feature is the flexibility in the program to assimilate and incorporate technology updates into the modules, on the fly. This program also comes with the benefit of Placement support from IBAX Minds though you would not have the need since opportunities galore when you do this program. And what more, this variant of the program comes with a Placement Assurance*.(*Terms & Conditions Applicable)

Duration : 12 Months (9 Months - Class Room & Online Training plus 3 months real time projects)

Class : Online Classes

Eligibility Criteria:

Graduate with any degree (mentioned below) from a recognized university with minimum of 55% aggregate

Working professionals with work experience and a graduate from a recognized university with minimum 50% aggregate in the below mentioned degrees

BE / BTech / ME / MTech / BCA / MCA
BA / MA - With Economics, Econometrics, Statistics & Mathematics
BSc / MSc - With Mathematics / Statistics as one of the subjects
BCom / MCom - With Mathematics / Statistics as one of the subjects
Any other Graduate with Mathematics/ Statistics as one of the subjects
Programming knowledge is desirable in any of the language for all the above disciplines

Course Fee: INR 150000 + Tax /-

Placements Scheme charges: INR 50000 + Tax /-

Placement Guarantee after completion of course fee appicable

Modules : Big Data 101, Statistics 101, R Programming, Python, Statistics with R, Advanced Statistics with R,Data Mining 1 - Machine Learning with R, Data Visualization with Tableau, Data Visualization with D3, Text Analytics, Web Analytics, RDBMS with SQL and DWH

Course Outline

Text Analytics

Basics of text analysis processes, Web crawling, web scraping from downloaded html files, text classification, singular value decomposition concept, Latent sematic Analysis, Document clustering, Topic modeling.


Understanding Basics of Python, Control Structures and for loop, Playing with while loop | break and continue, Strings and files, List Dictionary and Tuples.

R Programming

Introduction to R , Common Data Structures in R , Conditional Operation and Loops, Looping in R using Apply Family Functions , Creating User Definrd Functions in R,Graphics with R , Advanced Graphics with R

Statistics with R

Data, probability, discrete distribution, continuous distributions, linear and multiple regression, inference and estimation, inference and hypothesis testing

Data mining 1 / Machine learning with R

R,Loops in R, Concept of data structure in R, Creating Boolean index in R, Understanding Loops, R graphics, data clustering (k-means,hirerachial), Decision tree (C4.5 and CART), Concepts of Association Rule Mining, Building association rules and interpretation.

Data Visualization with Tableau

Tableau, Qlik View, Google Charts, Geomapping and Data from Quandl. R: Data visualization (GGplot 2) and Google visualization. Assignment: Blogpost

Advanced Statistics with R

Hypothesis testing-test, Analysis of Variance ( One and two way ANOVA),Chi-Square Analysis, Non-parametric Statistics, Linear and Multiple regression, Advanced Multiple Regression, Logistic Regression and Forecasting.

Big Data 101

Big Data Characteristics, Big Data and Business, Big Data Case Studies, Data Relationships and Data Model, Data Grouping, Clustering Algorithms, UPGMA Clustering Algorithm, Single Link Clustering Algorithm, KPIs and Businesses, KPIs and Data Elements, Mapping for business outcomes, Basic and Advanced Query.

Statistics 101

Introduction to Statistics , Introduction to Statistics - II ,Measures of Central Tendency, Spread and Shape -I,Measures of Central Tendency, Spread and Shape - II ,Measures of Central Tendency, Spread and Shape - III ,Measuring Association.

Web Analytics

Intro to Digital Media & Google Analytics , Audience , Acquisition & Behavior Analytics , Intro to Google Adwords Analytics & Managing a Google Analytics Account.

RDBMS with SQL and DWH

RDBMS, Data Modelling, SQL lite, DDL & DML, Data warehousing, Dimensional modeling

Data Visualization with D3

Selections , SVGs ,Data Binding ,Styling with D3,Scaling with D3 , Interactive Visualizations.

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