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M.Sc. in Computer Science

 

Overview

This innovative MSc in Computer Science course provides an opportunity for graduates from disciplines of Computer Science and Pure Sciences to develop knowledge and skills in the broad areas Computer Science with a special focus on Artificial Intelligence. The objective of this course is to help the students:

  • Develop into agile and skilled Computer Science professionals who are adept at working in variety of settings.
  • Be able to meet the challenges and reap the rewards of interdisciplinary team work.

The broad areas in which the students will be able acquire their skills and knowledge are: Data Base Management Systems, Operating Systems, Computer Networks, Principles of Programming Languages, Artificial Intelligence, Reinforcement Learning, Machine Learning, Deep Learning, Optimization Techniques and so on. It also involves use of state-of-the-art concepts and technologies in delivering knowledge, wherein languages like Python, Java, C and various visualization tools like Tableau will be effectively used in the delivery. The pedagogy is will be hands-on using real world case problems

[College Code: NKCGOIDGP]

M.Sc in Computer Science
Course Level Post Graduation
Duration 2 Years
Eligibility Graduation in STEM Subject
Type Degree

Scope & Career Opportunities

Following are some of the roles in the industry for Computer Science specialists with particular skill in Artificial Intelligence:

  • Software Analysts and Developers
  • Computer Scientists and Computer Engineers
  • Algorithm Specialists
  • Research Scientists and Engineering Consultants
  • Medical Health Professionals working with Artificial Limbs, Prothetics, Hearing Aids and Vision Restoration Devices.
  • Machine Learning Experts

Curriculum

Semester I

  • Principles of Programming Languages
  • Advanced Data Base Management Systems
  • Software Engineering
  • Discrete Mathematics
  • Numerical Methods
  • Advanced Data Base Management Systems Lab
  • Programming in C Lab

Semester II

  • Data Structures and Algorithms Design
  • Advanced Computer Architecture
  • Computer Networks
  • Object Analysis and Design
  • Optimization Techniques
  • Object Oriented Programming in Java Lab
  • Data Structures and Algorithms Lab

Semester III

  • Artificial Intelligence
  • Machine Learning
  • Reinforcement Learning
  • Natural Language Processing
  • Computer Vision
  • Programming in Python Lab
  • Machine Learning using Python Lab

Semester IV

  • Elective – I
  • Elective – II
  • Major Project
  • Grand Viva

Specializations

NSHM will provide the following advanced analytics courses as electives:

  • Deep Learning
  • Neuro, Fuzzy and Soft Computing
  • Evolutionary Computing
  • Bayesian Networks
  • Internet of Things
  • Cloud Computing

Special Deliverables

  • UGC approved bachelor degree program
  • State-of-the-art infrastructure for high performance computing that is ideally suited for analytics of Big Data, Data Science, Cyber Security, Internet of Things and Cloud Computing.
  • Analytics Society of India, Kolkata Chapter guided analytics learning and certification
  • Association with national level analytics forums like Analytics India Magazine and Analytics Vidhya.
  • Faculty with proven track records in Industry and academics with experience in various industry verticals of analytics and also in research and development and innovation
  • Association and academic collaboration with foreign universities
  • Industry-driven curriculum based on the latest trends in the ever changing and evolving fields of Data Science
  • Sessions with Industry experts
  • Training in participating in national level Hackathons on Data Science
  • Extremely well connected with industry which will lead to excellent placement.

Infrastructure / Knowledge Tools

  • State-of-the-art Laboratory and Infrastructure
  • Library with more than 10,000 books along with e-journals and e-magazines
  • Vastly experienced faculty members with more than 70 % awarded or enrolled Ph.D scholars
  • Huge Extra-curricular and Co-curricular engagement opportunities

Eligibility

Graduation in STEM Subject

 


Duration

2 Years (Full Time)


Placement

                                                                             

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