Admissions Open for 2022

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    M.Sc. in Data Science

    Description:

    M.Sc Data Science program designed and aligned with industry Standards and bench mark. It aims to provide a solid foundation in Mathematics, Statistics, Competitive Programming, Internship and Research to develop the younger minds to work as a team and improve programming and leadership skills. At the end of program, the learner can become a computer software expert and join in any software industry.

    Programme USPs

    • All courses are hands-on
    • Andragogical Teaching Methodology Aligned with Industry 4.0
    • Industry Mentor for every single student from III semester onwards
    • Group project during the third year
    • One Full Semester Internship in the relevant Industry

    Course Matrix

     

    Sem

    Discipline Core (DC)

    (Major/Minor)

    Open Elective

    (OE)

    Foundation Course (FC)

    Competence Course (CC)

    Total Credits

     

     

    I

    • Mathematics for Data Science(4)
    • Database Management (4)
    • Data Structures and Algorithms (4)
    • Introduction to

    Data Science (4)

     

     

     

     

     

    FC – I

    Introduction to IKS (3)

    CC-I

    English Language Skills (2)

    CC – II

    Professional Communication Skills (2)

     

     

    23

     

     

    II

    • Statistical Methods for Data Science (4)
    • Data Visualization (4)
    • Machine Learning (4)
    • Data Mining (4)

     

     

    OE-1 (3)

     

    FC – II

    Empirical Sciences in Pre Modern India (3)

     

    CC -III (2)

    Technical Proficiency Skills/ Professional Attitude

     

     

    24

     

    III

    • Data Engineering (4)
    • Elective – I (4)
    • Elective – II (4)
    • Elective – III (4)

     

    OE-1 (3)

     

     

     

    CC III : Foreign Languages (2)

     

    21

    IV

    • Dissertation / Internship (12)

     

     

     

    12

     

    60

    6

    6

    8

    80

    List of Electives

    Information Retrieval

    Bayesian Statistics

    Ethics for Data Science

    Natural Language

    Processing

    Real Time Analytics

    Big Data Systems

    Speech Recognition

    Optimization Methods

    for Analytics

    Data Warehousing

    Statistical Learning

    Deep Learning

    Spatial and Temporal

    Data Mining

    Time series

    Distributed Data

    Systems

    Graph Mining

    Artificial and Computational Intelligence

    Probabilistic Graphical Modeling

     

     

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