Batch start- 24 Feb...

Last date for registration17th Feb. Enroll now!

Post Graduate Program in Data Engineering – Visualization Placement Assured

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.

  • Duration36 weeks

  • EligibilityB.E / B.tech ( C.Sc, ECE, EEE) , MCA/MSC (C.Sc)

  • FEESRs.89400/-

  • Learning ModeFaculty-led Online

Course Highlights

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    Real-time Internship

    An internship allows you to apply classroom knowledge in real life situations. We help you find relevant work experience opportunities in organizations involved in Big Data Analytics.

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    Placement Support

    Our Placement Division helps our students meet companies that practice Big Data Analytics. Our Placement Division has positioned students in some of the top companies like Siemens, American Megatrends, Dell and HCL.

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    Training Methodology

    This course involves several hours of Live Faculty session and recorded live session. It also has multiple guest lectures every month. Along with live classes, the course has industry catalyzers, opinion polls, observers and self-assessments.

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    Capstone Projects

    During the course, the students pursue autonomous research on a question or problem of their choice, involve with the academic learning in the related disciplines, and - with the supervision of a faculty and industry mentor - produce a significant paper.

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    Industry Connect

    We connect you with industry leaders who play a major role in the Data and Analytics Domain. Connecting with such people can help you in job hunting, career networking and professional progress.

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    Learn through Case Studies

    Case studies help you to emphasize detailed contextual examination of a restricted number of events or circumstances and their relations. It helps in obtaining in-depth info about an individual, group, or occurrence.

Key Features of the Program

  • Effective & Appealing Content

    We offer a unique combination of research-led futuristic pedagogy and globally benchmarked content. Our modules are backed by extensive research which has made our education system both appropriate and exciting for our learners.

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  • Highly Experienced Faculty for Big Data

    At 361 DM, we have a group of highly qualified faculty from IIT Kanpur and IIT Kharagpur. Our faculties have worked with PwC and IBM and have years of experience in pioneering several Big Data and Analytics projects globally.

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  • Certification from Praxis Business School

    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.

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  • Education Loan

    Good Education ensures good future. We ensure your financial needs are taken care of as you move ahead in getting educated to build an awesome career. You can always apply for an Education Loan to join select courses.

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  • Internship

    An internship allows you to apply classroom knowledge in real life situations. We help you find relevant work experience opportunities in companies that look for Professionals skilled in Big Data Analytics.

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  • Placement Support

    Our Placement Support Entity helps our students meet companies that work with Big Data and Analytics. Our students have been placed in some of the top companies like Siemens, American Megatrends, Dell and HCL to provide meaningful placement support..

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  • New Age Learning Platform

    The i-meta platform of 361 DM, enabled with unique augmented and virtual reality-led classes allow mobile learning i.e., you can learn anytime and anywhere. You can also learn by downloading the 361DM App in your smartphone. Our platform facilitates group discussions, learning resources, performance records, post-class assessments, e-library, and opinion polls during classes.

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  • Dedicated Support Team

    We have a dedicated team to support you throughout the course – from the application to the certification! You can reach us whenever there is any need for assistance, just at the click of a button.

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Modules

Big Data 101

Big Data Characteristics

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

Big Data and Business

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

Data Grouping

Clustering Algorithms

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

Getting ready for Clustering Algorithms

Clustering Algorithms – UPGMA, single Link Clustering

KPIs, Businesses & Data Elements

Mapping for business outcomes

  • Define the pain point
  • Define the goal
  • Identify the actors
  • Identify the impacts
  • Identify the deliverables
  • Creating your impact map

Basic Query

Advanced Query – Embedding

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

Coding in DB Environment

Making Data Sets

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

R Programming

R Programming

Introduction to R – I

Introduction to R – II

Common Data Structures in R

Conditional Operation and Loops

Looping in R using Apply Family Functions

Creating User Defined Functions in R

Graphics with R

Advanced Graphics with R

Hadoop

Introduction to Big Data and Hadoop

Introduction to DBMS systems using MySQL

Big Data and Hadoop EcoSystem

HDFS

Unix & HDFS Hands-on

Map-Reduce

  • Basics
  • Advanced topics
  • Hands on

Pig

  • Introduction
  • Hands on
  • Scripting

Hive

  • Introduction
  • Metastore
  • Limitations of Hive
  • Comparison with Traditional Database
  • HIVE scripting
  • Hive Data Types
  • Partitioning and Bucketing
  • Hive Tables (Managed and External)

Scoop Introduction and Hands-on

Introduction to NoSql

HBASE

Access Methods

Big Data with Spark and Python

Python

Understanding Basics of Python

Control Structures and for loop

Playing with while loop | break and continue

Strings and files

List

Dictionary and Tuples

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

  • Traditional Visualization
  • Big Data Visualization

Tableau product offerings

Installation of Tableau Public

Working with Tableau - Live Case study/Discussion

Creating interactive dashboards with Tableau Public

Case study discussion

  • HR – Case Study with Data

Story Boarding with Tableau Public

Case study discussion

Geomapping in Tableau

  • Create a geographic hierarchy
  • Build a basic map
  • Change from points to polygons
  • Add visual detail
  • Add labels
  • Customize your background map

Qlik view – Basics

  • Download QlikView Personal Edition and Install

Google charts – Basics

  • Creating a simple Google Chart with in data
  • Image generation, Line, bar, and pie charts.
  • Scatter plot
  • Google-o-meter
  • Map,Radar,Venn diagram
  • Specification of attributes

Dynamic charts with Google Docs

  • Using Google Docs as database to store graphical data
  • Specifying the range of data and selecting columns
  • Creating an interactive Google Chart with Google Docs data

Supplementary material & Case study discussion

Closing session & Queries

Data Visualization with D3

RDBMS with SQL and DWH

Introduction to DBMS / RDBMS

Data Modelling

Physical Data Model

Getting Started with SQL Lite

DDL

DML

Introduction to Data Warehousing

Dimensional Modelling

Advanced SQL

Olap Cubes

Olap Cubes Practicals

Outcome of the Program

Advanced Business Analytics 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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About the Praxis

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.

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