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Helpline no. 0129-4259000

Helpline no. 0129-4259000


Integrated M.Sc. Data Science & Analytics

About the Program

The “Integrated M.Sc. in Data Science and Analytics” is a 5 Year integrated degree Programme with multiple exit and entry options offered by the Department of Sciences(Mathematics) from the academic year 2024-2025 and onwards.

It is an interdisciplinary programme covering courses from the areas of Mathematics, Statistics and Computer Science that provides a comprehensive skill set to analyze, contextualize, and draw insights from the data through technological interventions. A perfect amalgamation of foundation, advanced, professional and industry based courses both as core & electives supplemented with internships, workshops, industrial visits prepares a student to meet global standards.

The program is highly promising as it caters the need to be a Data Scientists, Data Analyst, Data Manager, Data Architect, Data Engineer, Business Analyst, Software Engineer, Machine Learning Engineer etc. and also prepares them for pursuing higher studies.


Duration 5 Years
Fees 180000/-
Eligibility Criteria Minimum 50% marks or equivalent CGPA in 12th with Mathematics as a compulsory subject
Merit Preparation for Admission Merit preparation / short listing of candidates shall be on the basis of score in MRNAT 2024 /Marks in Qualifying Examination


Program Educational Objectives:

Preparation : A broad general education ensuring an adequate foundation in Basic Sciences, and English language

Core Competence : A solid understanding of concepts fundamental to the discipline of Sciences.

Breadth : Good analytical skills, design and implementation of science experiments required to solve current scientific and society problems.

Professionalism : The ability to function and communicate effectively the key knowledge base and laboratory resources careers as professionals.

Learning Environment : To provide student awareness of the Sciences as an integral activity for addressing social, economic, and environmental problems, and fostering important skills for job as well as for higher studies.

Programme Outcomes (POs)

PO1. Knowledge in Mathematics and Data Science: Understand the basic concepts, fundamental principles and the scientific theories related to Data Science & Analytics.

PO2. Abstract thinking: Ability to absorb and understand the abstract concepts that lead to various advanced theories in Mathematics, Statistics and Computer science.

PO3. Problem analysis and design solutions: Ability to identify, analyze and design solutions using fundamental principles of mathematics, Statistics, computing sciences, and relevant domain disciplines.

PO4. Advanced theories and methods: Understand advanced theories and methods to design solutions for complex Data Science & Analytics problems.

PO5. Applications in Engineering and Sciences: Understand the role of mathematical sciences and apply the same to solve the real life problems in fields of Data Science & Analytics.

PO6. Modern software tool usage: Acquire the skills in handling scientific tools towards problem solving and solution analysis.

PO7. Environment and sustainability: Understand the significance of preserving the environment towards sustainable development and proposing sustainable solutions.

PO8. Ethics: Imbibe ethical, moral and social values in personal and social life leading to highly cultured and civilized personality. Continue to enhance the knowledge and skills in mathematics and computer science for constructive activities, and demonstrate the highest standards of professional ethics.

PO9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

PO10. Communication: Develop various communication skills such as reading, listening, and speaking which will help in expressing ideas, views clearly and effectively.

PO11. Project Management, Research &  Innovation: Demonstrate knowledge, understand the scientific and management principles and apply these to one‘s own work, as a member/ leader in a team to manage projects and multidisciplinary research environments. Also use the research-based knowledge to analyze and produce innovative solutions based on global needs and trends.

PO12. 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.


Programme Specific Outcomes (PSO’s)

PSO1. Utilize the data science theories for societal and environmental concerns.

PSO2. Understand and commit to professional ethics and cyber regulations, responsibilities, and norms of professional computing practices.

Key Highlights of the programs:

  • Latest program & curriculum as per Industry demand
  • CBCS (Choice Based Credit System) & NEP 2020 implemented
  • Multiple exit & entry options
  • Exit option after 1 years—Undergraduate Certification in Data Science & Analytics
  • Exit option after 2 years— Undergraduate Diploma in Data Science & Analytics
  • Exit option after 3 years—B.Sc.  in Data Science & Analytics
  • Exit option after 4 years— B.Sc. in Data Science & Analytics with  Honours/Research/Post-Graduate Diploma in Data Science & Analytics
  • Exit option after 5 years—  M.Sc. in Data Science & Analytics


  • Industry oriented courses and projects – a wide range of core and open elective courses
  • Compulsory Project work
  • MOOC/NPTEL Courses
  • State of the art academic and research laboratories.
  • Career Skills sessions for Placements & competitive exams.
  • Mentoring students for National Level Hackathon, technical contests and symposiums.
  • Regular Invited Expert Lectures & Workshops from Academia & Industry. Webinars on specialized topics in Data Science by Professors from IITs, IIMs, IISCERs, IIITs, NITs and research labs from industries such as IBM, and Microsoft.

Class room teaching supplemented with labs/internships/projects etc. further strengthens the foundation of the course in student’s understanding.

Program Structure

Scheme & Syllabus

Year Semester Credits
I I 21
II 22
IV 20
III V 18
VI 20
V IX 20
X 18
Total Credits 203


Scope of Employment, Placements & Higher Studies:

This program helps students to become Data Analysts & Scientists and also prepares them for pursuing higher studies.

Employment Area

  • Data Scientist
  • Data Analyst
  • Data Manager
  • Data Architect
  • Data Engineer
  • Business Analyst
  • Software Engineer
  • Machine Learning Engineer
  • Statisticians
  • IT & Tech, Business firms and Consultancies
  • Banking, Financial Services and Insurance(BFSI) sector
  • Pharma and Healthcare
  • E-commerce
  • Telecom Industry
  • Automobile Industry
  • Digital Marketing
  • Travel and Hospitality
  • R&D firms

Higher Studies

After B.Sc.– M.Sc. Data Science & Analytics, M.Sc. Applied Mathematics, M.Sc. Statistics, Software Engineering, Cyber Security, MBA in Business Analytics, Data Analytics &  E-Business etc. MCA, MBA

After M.Sc. – M.Tech. Computer Science, Ph.D.



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