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:
- An ability to analyze a problem, and identify and define the computing requirements including operating systems appropriate to its solution and apply the knowledge of computing.
- An ability to analyze, design, implement, and evaluate a computer-based system, process, component, or program to meet desired needs and to function effectively on teams to accomplish a common goal
- An ability to analyze, design the storage and security requirements for software development
- Knowledge to develop online as well as offline projects having remote access to databases and programs and expertise in the current trends or latest industry needs
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
