Professional Certificate Program in Business Analytics

Duration : 3 Months

Certificate Program in Business Analytics

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Data Science with IIKMBA

Professional Certificate Program in Business Analytics

Evolved and designed by veterans in the Analytics industry, this program prepares students and working professionals, especially people from Non tech background (from Business, Statistics, Math) to start or improve upon a 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. While we cover Technology and coding to an extent, it is designed in such a way it is non intrusive for a person from Non Tech background and allows them to focus on their areas of strength like Stat, Business analytics. Needless to say, there cannot be a better opportunity that this for the Business/Statistics professionals to take a big leap in their career.

Duration : 3 Months

Class : Weekend Classroom

Eligibility : B.E / B.Tech / MBA / UG - PG with (Mathematics / Statistics) from a recognized university

Course Fee: INR 50000/-

Modules : Big Data 101, Statistics 101, R Programming, Statistics with R, Data Mining 1 - Machine Learning with R, Data Visualization with Tableau, RDBMS with SQL and DWH

Projects : Live Projects(Optional)

Course Outline

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.

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 Visualization with Tableau

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

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.

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

RDBMS with SQL and DWH

Introduction to DBMS / RDBMS, Data Modelling - Entity Relationships Data Modelling - Normalization, Physical Data Model, Getting started with SQL lite, DDL (Creating Tables, Loading Data, Insert, Delete,Update) & DML, Data warehousing, Dimensional modeling.

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