Post Graduate Program in Data Engineering (Visualization)

with Placement Assurance---Duration : 12 Months

Data Engineering (Data Visualization)

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Data Science with IIKMBA

Post graduate program in Data Engineering (Data Visualization) with Placement Assurance

Evolved and designed by veterans in the Analytics industry, this program prepares students and working professionals 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. This is a career oriented program that covers all the key aspects of Data Engineering. 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.

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

Class : Online Classes

Eligibility : B.E / B.Tech (CSE, IT, EEE, ECE, E&I) from a recognized university

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, Hadoop, Access Methods, Big Data with Spark and Python,Python, Data Visualization with Tableau, Data Visualization with D3, RDBMS with SQL and DWH

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.


Introduction to Big data and Hadoop, Hadoop Architecture, Hadoop Deployment, Hive - Introduction, Metastore, Hive data types, Partitioning and Bucketing, Mapreduce Framework , Hbase Architecture - Run models & Configuration, Hbase Cluster Deployment, Data Model, HBase Shell, Data Loading Techniques

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

Data Visualization with Tableau

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

Data Visualization with D3

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

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.

Access Methods

Sqoop,Flume,Pig,Zookeeper, Oozie and Apache Spark.

Big Data with Spark and Python

Python: Data Structure, Twitter Analysis and Analytics, Text Analytics, Hadoop. Spark: Machine Learning with Spark Case Studies: Python + Spark Project: Spark.


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

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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