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Master of Science in Computer Science

2 Years Master Degree Programme

Faculty

Faculty of Engineering and Technology

Programme Type

Master Degree Programme

Duration

2 Years

Eligibility

Minimum 60% in B.Sc....

Overview of the Programme

The programme M.Sc in Computer Science (Specialization: Artificial Intelligence/ Data Science) aims at meeting the demands of the R&D sector related to Intelligent Systems of the modern society, giving in-depth knowledge about Pattern Recognition, Data Analytics, Machine Learning, Soft Computing, Human-Computer Interaction, and related areas. The programme focuses on the creation and application of methods for collecting, organizing, analyzing and making discoveries from any source and volume of data; making students expert in areas like Machine Learning, Data Mining, Big Data Analytics etc.

Programme Outcomes

PO1: Basic Knowledge of Artificial Intelligence & Data Science: Apply knowledge of Mathematics, Statistics, Artificial Intelligence, and Data Science concepts to the solution of ICT problems.

PO2 : Design & Development of ICT Solutions: Design and development of ICT solutions for Artificial Intelligence and/or Data Science problems using state-of-the-art te ...

PO1: Basic Knowledge of Artificial Intelligence & Data Science: Apply knowledge of Mathematics, Statistics, Artificial Intelligence, and Data Science concepts to the solution of ICT problems.

PO2 : Design & Development of ICT Solutions: Design and development of ICT solutions for Artificial Intelligence and/or Data Science problems using state-of-the-art techniques that meet specified needs with appropriate consideration for cultural, societal and environmental considerations.

PO3 : Modern Tool Usage: Create, select and apply appropriate techniques, resources and modern Artificial Intelligence and Data Science tools including prediction and modelling with an understanding of the limitations.

PO4 : Environment and Sustainability: Understand the impact of professional ICT solutions in societal and environmental contexts and demonstrate knowledge of and need for sustainable development.

PO5 : Ethics: Apply ethical principles and commit to professional ethics, responsibilities and norms.

PO6 : Individual and Team Work: Function effectively as an individual, and as a member or leader in diverse teams and in multi-disciplinary settings.

PO7 : Communication: Communicate effectively with society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations and give and receive clear instructions.

PO8 : Project Management and Finance: Demonstrate knowledge and understanding of Software Engineering and Project management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.

PO9 : Life-long Learning: Recognize the need for and have the preparation and ability to Engage in independent and life- long learning in the broadest context of technological Change.

Course Structure

Semester 1

Course NameCourse CodeCredit
COMPUTER NETWORKSMCS1014
DATA STRUCTURE AND ALGORITHMMCS1024
PROBABILITY AND STATISTICSMCS1034
COMPUTER ORGANIZATION AND ARCHITECTUREMCS1044
DATA STRUCTURE AND ALGORITHM LABMCS1121
R- PROGRAMMING LABMCS1131

Semester 2

Course NameCourse CodeCredit
OPERATING SYSTEMMCS2014
DATABASE MANAGEMENT SYSTEMMCS2024
OBJECT-ORIENTED PROGRAMMING USING JAVAMCS2034
DATABASE MANAGEMENT SYSTEM LABMCS2121
OBJECT-ORIENTED PROGRAMMING USING JAVA LABMCS2141
ELECTIVE-I(ARTIFICIAL INTELLIGENCE FUNDAMENTALS)MCSAI2044
ELECTIVE-I (DATA SCIENCE FUNDAMENTALS)MCSDS2044

Semester 3

Course NameCourse CodeCredit
PYTHON PROGRAMMINGMCS3014
MACHINE LEARNINGMCS3024
PYTHON PROGRAMMING LABMCS3111
PROJECT-IMCS3215
ELECTIVE-II (NEURAL NETWORK AND DEEP LEARNING)MCSAI3034
ELECTIVE-II (STATISTICAL FOUNDATION FOR DATA SCIENCE)MCSDS3034

Semester 4

Course NameCourse CodeCredit
PROJECT-IIMCS42110
ELECTIVE-III (PATTERN RECOGNITION)MCSAI4014
ELECTIVE-V (EXPERT SYSTEM)MCSAI4024
ELECTIVE-III (BIG DATA ANALYTICS)MCSDS4014
ELECTIVE-II (DATA VISUALIZATION)MCSDS4024

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