M.Sc. Computer Science (Data Science)

Programme Overview
The Post Graduate Department of Computer Science offers Master of Science in Computer Science (M.Sc) with specialization in Data Science. The Programme aims to develop core competence in Computer Science with respect to the Data Science discipline and prepare the students to take up a career in the highly competitive IT industry as well as carry out research and development. The programme comprises of full-time four semesters including a Major project in the fourth semester. The programme creates and nurtures data science professionals with a seamless blend of Machine Learning, Big Data Analytics and Statistics with strong methodological foundations in decision sciences, research and industry oriented applications from a global perspective.

Eligibility
The candidate with B.Sc. (Computer Science) or BCA with Mathematics as one of the subjects and at least 50% marks taken together of all optional subjects or B.Sc. (PCM) graduates with P.G. Diploma / Certificate Course in Computer Science of one-year duration are eligible.

Training beyond Curriculum
Formal classroom sessions are supplemented with frequent guest lectures by experts from the industry and academia. To give a more professional impetus to the training programme, Student Seminar Series, International Lecture Series, Tech Talk Series, Industry Institute Interface (3i) sessions, Webinars, Technological Transformation from Industrial experts and workshops are arranged on various topics such as contemporary developments in computer technology, group dynamics, leadership and managerial skills, presentation skills, human relation and teamwork, etiquette, etc. In addition to these, students are trained effectively to take part and excel in Inter-collegiate IT competitions that are conducted at regional and national levels.

Knowledge Enrichment Programmes
The Department believes that Data Science is a rapidly evolving discipline. It is important that we contribute to global information technology in a way that our students can devote themselves to take the maximal advantage of emerging Data Science trends to solve a wide range of technological problems based on their interest / specialization. The objective is to hone technical skills demanded by today's professionals by providing a sound technical platform and the required knowledge base. It prepares the students to meet the challenges faced by today's IT professional by exposing them to wide array of cutting-edge technologies.

The technical community of the Department is headed by a faculty member. Students can be members of these communities after their first semester. Students can select their own specialization, and improve their skills. Knowledge enrichment is ensured through Seminars, Guest Lectures, Workshops, Industrial Visits, Quiz Programmes, Paper Presentations, etc.

Industry Expert Training Programme
The contents of certain courses are delivered to the students by the trainers from leading MNCs. The trainers who have excellent experience of imparting subject information clearly and concisely are identified for courses like Agile and DevOps, Data Analytics and Software Testing Tools. It helps the students to enrich their knowledge at a deeper level and in par with the industry trends.

IEEE Student Branch (School code- STB18221)
IEEE student branch of the department of computer science (PG) provides a forum for students to participate in professional, technical, and social activities beyond the campus. It also provides an opportunity for them to begin networking in their areas of study. Some activities that the student Branch has undertaken in the recent years are design competitions, designing of a student branch website or Global Student Website, tutorials for non-members, participating in IEEE conferences and participating in engineering awareness programs.

Industry Mentorship Programme
The Industry Mentorship Programme [IMP] is a collaborative effort sharing programme both in time and knowledge by the mentor from the industry and an in-house faculty member. Mentors share their Knowledge through offline or online streams and invite the students to visit their organization for seminar or any of the technical discussions. Students will be completing the work assigned by their respective mentors in a stipulated time monitored by the in-house faculty.

Software Development Cell
The Software Development Cell provides opportunities for the emerging software professionals to actively participate in the real time Software Development process. It helps to identify the suitable standardized platform for building up proper entrepreneurial skills. The mission is to undertake software development tasks from external agencies and provide best quality services in time. The cell also undertakes in-house digitalization assignments.

Membership in Professional Bodies
The Department of Computer Science (PG) is a member of Institute of Electrical and Electronics Engineers (IEEE), Computer Society of India (CSI), Association for Computing Machinery – Women (ACM –W). Faculty members are also members of the Indian Science Congress Association, ACM-W and IEEE.

Industry – Academia Alliance
The Department leverages Industry- Academia Alliance with AWS, DELL-EMC, ICT, SODA Foundation and ORACLE to prepare the young talents for successful careers in the new IT landscape.

Draft Course Matrix
I Semester
Java and Web Programming
Software Engineering
Mathematical Foundations for Data Science
Advanced Database Management System
Data Structures and Algorithms
Java and Web Programming Practical
Data Structures and Algorithms Practical
Soft Skills

II Semester
Machine Learning
Middleware Technologies
Statistical Methods Using R
Data warehousing and Multidimensional Model
Machine learning Practical using Python
Software Engineering Mini Project
Elective I:
Ethics in Data Science
Theory of Computing
Cloud Computing
.NET Programming Practical

III Semester
Artificial Intelligence
Data Science and Big Data Analytics
NoSQL Databases
MATLAB Programming
NoSQL Databases Project
Generic Elective
Elective II:
Sentiment Analysis
Image and Video Analytics
Business Analytics
Research Methodology

IV Semester
Deep Learning
Major Project
Natural Language Processing
Elective III:
Distributed Computing
Soft Computing
Data Visualization

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