MSc Data Analytics

Program Overview

Career Opportunities

After completion of Under Graduate and Post Graduate programmes offered by the department of computer science, the students get the world of opportunities in various categories as follows:

  • IT organizations
  • All Banking / Financial institutions
  • IOT & its development
  • Firmware development
  • ITES organizations
  • Mobile Applications Development
  • Software / Hardware Entrepreneurship
  • Teaching / Professional sector
  • All Governmental positions which need Group-I examinations
  • Research and Development (R & D) of IT sector

Programme USPs

  • Most attractive courses with high caliber and lucrative career opportunities in data science and other trending technologies.
  • A Plethora of career opportunities in various IT Sectors as well as other Government sectors throughout the globe.
  • Progression to higher studies in various disciplines and Research Programmes in thrust areas.

Programme Outcomes

Upon completion of the programme, the students are expected to have acquired:

  • Ability to apply knowledge of Computer Science, Mathematics and Statistics to solve problems.
  • Ability to model, analyze, design, visualize and realize physical processes of Big
    Data.
  • Ability to select appropriate methods and tools for data analysis in specific
    organizational contexts.
  • Ability to analyze very large data sets in the context of real world problems and
    interpret results.

Eligibility Criteria

A pass in any Bachelor’s degree of minimum 3 years duration with Mathematics or Statistics as any one of the subjects at Graduate level

Programme Duration

2 YEARS (4 SEMESTERS)

Programme Type

Regular

Programme Structure

SEMESTER I

  • Principles of Data Science
  • Mathematics for Data Analytics
  • Design and Analysis of Algorithms
  • Python Programming
  • Python Programming lab
  • Modular: Module I – Course I: Advanced Excel
  • Modular: Module I – Course II:  Advanced Excel Lab

SEMESTER II

  • Advanced Database Management Systems
  • Operations Research
  • Data Analytics using R
  • Machine Learning
  • Advanced DBMS Lab
  • Programming Lab in R
  • Modular: Module II – Course I: LaTeX
  • Modular: Module II – Course II: LaTeX Lab

SEMESTER III

  • Cloud Computing
  • Multivariate Analysis
  • Big Data Frameworks and Tools
  • Big Data Tools Lab
  • Mini Project
  • Modular: Module II – Course III : UI/UX Design
  • Modular: Module III – Course I: UI/UX Design Lab

SEMESTER IV

  • Data Visualization
  • Data Visualization Lab
  • Project
  • Modular: Module III – Course II: MATLAB
  • Modular: Module III – Course III: MATLAB Practicals

Credits & Evaluation

  • Semester-wise/ year-wise
  • Date of the last semester-end / year-end (for non-semester) examinations
  • Date of declaration of results of semester-end/ year-end examinations
  • Number of days taken for declaration of results for semester-end/ year-end examinations
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