Data Science is popular in all academia, business sectors, and research and development to make effective decision in day to day activities. MSc in Data Science is a two year programme with four semesters. This programme aims to provide opportunity to all candidates to master the skill sets specific to data science with research bent. The curriculum supports the students to obtain adequate knowledge in theory of data science with hands on experience in relevant domains and tools. Candidate gains exposure to research models and industry standard applications in data science through guest lectures, seminars, projects, internships, etc.


Programme Objective

• To acquire in-depth understanding of the theoretical concepts in statistics, data analysis, data mining, machine learning and other advanced data science techniques.
• To gain practical experience in programming tools for data sciences, database systems, machine learning and big data tools.
• To strengthen the analytical and problem solving skill through developing real time applications.
• To empower students with tools and techniques for handling, managing, analyzing and interpreting data.
• To imbibe quality research and develop solutions to the social issues.

Ethics and Human Values

1. Only proprietary or open source software would be used for academic teaching and learning purposes.
2. Copying of programs from internet, friends or from other sources is strictly discouraged since it impairs development of programming skills.
3. Unique Practical (Domain based) exercises ensures that the students don’t involve in code plagiarism.
4. Projects undertaken by students during the course are done in teams to improve collaborative work and synergy between team members.
5. Projects involve modularization which initiates students to take individual responsibility for common goals.
6. Passion for excellence is promoted among the students, be it in software development or project documentation.
7. Giving due credit to sources during the seminar and research assignment is promoted among the students
8. The course and its design enforce the practice of good referencing technique to improve the sense of integrity.
9. Courses involving group discussions and debates on ethical practices and human values are designed to sensitize the students in dealing with customers and members within the organization.


On successful completion of the MSc programme students will be able to
PO1    Engage in continuous reflective learning in the context of technology and scientific advancement.
PO2    Identify the need and scope of the Interdisciplinary research.
PO3    Enhance research culture and uphold the scientific integrity and objectivity
PO4    Understand the professional, ethical and social responsibilities
PO5    Understand the importance and the judicious use of technology for the sustainability of the environment
PO6    Enhance disciplinary competency, employability and leadership skills

Programme Specific Outcomes for MSc (Data Science)

PSO1: Abstract thinking: Ability to understand the abstract concepts that lead to various data science theories in Mathematics, Statistics and Computer science.

PSO2: Problem Analysis and Design Ability to identify analyze and design solutions for data science problems using fundamental principles of mathematics, Statistics, computing sciences, and relevant domain disciplines.

PSO3: Modern software tool usage: Acquire the skills in handling data science programming tools towards problem solving and solution analysis for domain specific problems.

PSO4: Innovation And Entrepreneurship: Produce innovative IT solutions and services based on global needs and trends.

PSO5: Societal And Environmental Concern: Utilize the data science theories for societal and environmental concerns.

PSO6: Professional Ethics: Understand and commit to professional ethics and cyber regulations, responsibilities, and norms of professional computing practices.

PSO7: Conduct Investigations of complex computing problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.

PSO8: Individual and Team work: Function effectively as an individual and as a member or leader in diverse teams and in multidisciplinary environments.

PSO9: Applications in Multi disciplinary domains: Understand the role of statistical approaches and apply the same to solve the real life problems in the fields of data science.

PS10: Project Management: Apply the research-based knowledge to analyse and solve advanced problems in data science.


Open Electives