Program Card
Praxis logo

PGP in Data Science and Data Visualization

Program Highlights:
Mentorship Support, Resume Preparation,Praxis Certification, Tech Update Sessions, Real Time Internships, Industry Projects

E 3

PGP in Data Science and Data Visualization

This Post Graduate Program in Data Science and Data Visualization – designed by veterans in the Analytics industry; helps to establish a decent career in the growing Data and Analytics domain. This uniquely blended Program is brought to you by Praxis, a Top-ranked Analytics B-School in India.

Sneak Peak

INR 59,600

Program Summary

  • 30 credits
    Credits

    With this course, you are 5 credits short of an assured placement.

    Learn more
  • Duration 1 Year
  • 95 Hours of projects/Assignments
  • 185 Hours of online sessions

Course Topics

  • 1

    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

    • 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
  • 2

    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

  • 3

    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

  • 4

    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

    • Map Reduce Advanced Topics and Hands on

    • Pig introduction and Hands on

    • Pig Scripting

    • Hive Introduction, Metastore, Limitations of Hive

    • Comparison with Traditional Database and HIVE scripting

    • Hive Data Types, Partitioning and Bucketing

    • Hive Tables (Managed and External)

    • Hive Continued

    • Scoop Introduction and Hands-on

    • Introduction to NoSql and HBASE

    • HBASE architecture and Hands-on

  • 5

    Access Methods

  • 6

    Big Data with Spark and Python

  • 7

    Python

    • Understanding Basics of Python

    • Control Structures and for loop

    • Playing with while loop | break and continue

    • Strings and files

    • List

    • Dictionary and Tuples

  • 8

    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

  • 9

    Data Visualization with D3

  • 10

    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

Industry Connect

  • G Infotech Logo

    We are elated by the program methodology, content, people and the platform of 361 DM which instills confidence in the quality of candidates emerging out of this program. As a techprenur, I look forward for such candidates who could partner in our growth


    -Praveen, Director, G Infotech

    Aaum Analytics

    This product is endorsed by Aaum Analytics.

    A company specialised in analytics with strong focus on research and technology

    Program Card

    Being a Business Anthropologist, I largely work on Data and its Science for areas like HR Analytics, Market Research Analytics, Culture Research & Consulting. I find the programmes very diligently designed to meet the industry needs and for consultants like us. Great work by the team.


    -GV Suresh, CEO

  • Capegemini

    As an Industry person with over 20 years of experience,I have witnessed multiple training programmes and training providers.This program of 361DM stands out from all of them for the expertise of professionals delivering, the quality of the content and the engaging model of the platform.Truly Enriching! - Vijay-Project Manager-Capgemini


    - VijayKumar, Senior Manager, Capegemini

Program Mentors

Learn from the best in the industry

Browse Courses