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Professional Certificate Program in Big Data Technologies

Program Highlights:
Praxis Certification, Placement Support, Tech Update Sessions, Real Time Internships, Industry Projects

E 4

Professional Certificate Program in Big Data Technologies

This Program has a perfect blend of Technology, Data Science and Business cases and insights; stands out to be among the best in the world. This uniquely blended Program is brought to you by Praxis, a Top-ranked Analytics B-School in India.

Sneak Peak

INR 35,000

Program Summary

  • 20 credits
    Credits

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

    Learn more
  • Duration 6 months
  • 60 Hours of projects/Assignments
  • 149 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

    Big Data with Spark and Python

  • 5

    Python

    • Understanding Basics of Python

    • Control Structures and for loop

    • Playing with while loop | break and continue

    • Strings and files

    • List

    • Dictionary and Tuples

  • 6

    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

  • 7

    Access Methods

  • 8

    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

    Oracle

    Would like to endorse for this 12 month Post Graduate Program in Data Science

    -Bains,Accounting Manager, Oracle

  • Infodrive Analytics

    very good on trainings

    -G.Karpagavalli, Sr Manager - HR

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