Qualification File_PG-DBDA.pdf

PG-Diploma in Big Data Analytics (PG-DBDA)

  • Originally Approved
  • Last Revised
  • Code2017/ITES/CDAC/01793
  • SectorIT-ITeS
  • Notional Hours900
  • Accrediting BodiesCentre for Development of Advanced Computing (C-DAC)
  • Certifying BodiesCentre for Development of Advanced Computing (C-DAC) organization of the Ministry of Electronics and Information Technology, Govt. Of India
  • Proposed Occupation

    The theoretical and practical mix of the Post Graduate Diploma in Big Data Analytics (PG-DBDA) programme has the following opportunities:

    • Big data analytic domain.
    • Analyze the big data using intelligent techniques.
    • Search methods and visualization techniques.
    • Applications using Map Reduce Concepts
    • Data analysis component for better understanding of the theoretical concepts from statistics, economics and related disciplines.
    • Industrial research projects for the development of future solutions in the domain of data analytics to make an impact in the technological advancement.
    • Advanced analytical tools/ decision-making tools/ operation research techniques to analyze the complex problems and get ready to develop such new techniques for the future.

    Cloud computing, accessing resources and services needed to perform functions with dynamically changing needs.

  • International Comparability

    Course which covers programming languages, Scala, Hadoop, Data Visualization, Business Decision and Analytics concepts in six months full time courses are not available. Various institutes are running courses but as masters programs or subset of this courses like:


  • Progression Pathway

    These candidates will be trained in software Engineering methodology, Project development and Management skills. 
    They can start career as Big Data technologies, Data Scientist and leads to project manager after having relevant experience.

  • Qualification File Qualification File_PG-DBDA.pdf
  • Supporting Documents
  • Formal structure of the qualification
    Title of unit or other component Mandatory/ Optional Estimated size (Hours) Level
    Statistical Analysis with R Mandatory 100 8
    Programming with Python Mandatory 50 8
    Fundamentals of Linux Programming Mandatory 40 8
    Java with Scala Mandatory 80 8
    Cloud Computing & Operations Mandatory 30 8
    Data Collection and DBMS (Principles, Tools & Platforms) Mandatory 80 8
    Big Data Technologies Mandatory 130 8
    Data Visualization - Analysis and Reporting Mandatory 40 8
    Business Decisions and Analytics Mandatory 50 8
    High Performance Computing Solution & Applications Mandatory 20 8
    Practical Machine Learning Mandatory 60 8
    Aptitude & Effective English Mandatory 100 8
    Project Mandatory 120 8
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