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The Department of Mathematics offers two-year M.Sc. program in Applied Statistics and Data Analytics and intends to provide students with strong foundation in statistical methodology, its applications, use of statistical computing packages and the skills to collaborate on projects to support the analysis and interpretation of statistical data in order to deal with the massive amounts of data generated by business, healthcare, sensors, the Internet, surveys, social media, astronomy, human space exploration and operations, and aeronautics.
The program provides a significant opportunity for independent study and research through project work, leading to a dissertation. The project work involves literature surveys, investigations, and contributions to specific areas of Mathematical Sciences. The resulting dissertation is expected to produce a research article suitable for publication in a reputable journal, and it is believed to greatly assist aspirants planning for a PhD.
The student exchange program is another crucial feature that enables students to explore higher study possibilities in top universities in the USA and Europe. Our students are currently pursuing PhD programs in prestigious institutions both within and outside India.

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Program Highlights

The curriculum includes cutting-edge topics like Big Data Analytics, Machine Learning, Pattern Recognition, and Marketing Analytics. Students are encouraged to enroll in an internship or in-plant training program during summer and/or winter vacations. In fact, the program is designed to blend the power of statistical analysis with the advent of computing facility in providing solutions to the challenging problems of aforementioned domains.
This course provides students an overview of machine learning algorithms and techniques for predictive modelling by understanding the principles and applications of supervised and unsupervised machine learning methods.
This program primarily focusses on the application of Statistics to almost each and every discipline and is efficient to meet the demands of today’s world be it Big Data, Machine Learning, Data Mining or any other field.

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Career Opportunities

A postgraduate (PG) degree in Applied Statistics and Data Analysis opens up various career opportunities in industries that rely on data-driven decision-making.
Some potential career paths for individuals with a PG degree in Applied Statistics and Data Analysis are Data Analyst, Statistician, Data Scientist, Business Intelligence Analyst, Market Research Analyst, Financial Analyst etc.
By acquiring this course they have opportunities to contribute to the field of statistics and data analysis through academic research, publishing papers, and staying updated on the latest advancements in the field.

Attention Please!

Amrita Vishwa Vidyapeetham has not appointed any Agent or Third-Party Client for securing admission in any programme. Students are hereby requested to contact only the toll-free number on our website for any admission related queries.

– Issued In Public Interest By Directorate Of Admissions And Academic Outreach




A pass in B. Sc. in Mathematics/ Statistics or B. Sc. in Computer Science with courses in Mathematics and/or Statistics with 50% marks in each course and an aggregate of 60%

Selection process

Test followed by interview.

Eligibility Criteria (Coimbatore)

A pass in B.Sc. in Mathematics/ Statistics or B.Sc. in Computer Science with courses in Mathematics and/or Statistics with 50% marks in each course and an aggregate of 60%

Selection process

Selection for the postgraduate program is based on a thorough evaluation of candidates’ performance in their undergraduate examinations.



2 Years – 4 Semester


Graduation in Mathematics or Mathematics as main with an aggregate minimum of 50% excluding language subjects


Selection will be based on merit and interview process.

Commencement of Application Form: March 12th, 2024


Semester 1
Course code Course L T P Credit ES
22MAT521 Data Structures and Algorithms 3 0  2 4 C
22MAT522 Introduction to  Data Analytics with R Programming 3 0 2 4 E
22MAT523 Linear Algebra 3 0 2 4 A
22MAT524 Optimization Techniques 3 1 0 4 D
22MAT525 Probability Theory and Estimation 3 0 2 4 B
22MAT526 Python Programming 3 0 2 4 F
21CUL501 Cultural Education 2 0 0 P/F G
  Total   24  
Semester 2
Course code Course L T P Credit ES
22MAT527 Big Data Analytics and Hadoop 3 0 2 4 D
22MAT528 Database Management 3 0 2 4 F
22MAT529 Data Mining 3 1 0 4 E
22MAT530 Machine Learning 3 0 2 4 C
22MAT531 Multivariate Statistics and Regression Analysis 3 0 2 4 B
22MAT532 Statistical Inference and Design of Experiments 3 0 2 4 A
21AVP501 Amrita Value Programme 1 0 0 1 G
22AVP103 Mastery Over Mind 1 0 2 2
Total 27
Semester 3
Course code Course L T P Credit ES
22MAT621 SQC and Reliability Theory 3 0 2 4 A
22MAT620 Deep Learning 3 0 2 4 B
Elective I 3 0 0 3 D
Elective II 3 0 0 3 E
Elective II 3 0 0 3 F
22MAT693@ Live-in-Lab.@/ Open Elective* 2 0 0 2 J
Total 19
Semester IV
Course code Course L T P Credit ES
22MAT695 Dissertation 10 P
  Total   10  

Total credits for the program: 80

@ Course code for Live in Lab

*One Open Elective course is to be taken by each student, in the third semester, from the list of Open electives offered by the School.

@Students undertaking and registering for a Live-in-Lab project, can be exempted from registering for the Open Elective course in the third semester.

Electives (any three)
Course code Course L T P Credit ES
22MAT731 Business Analytics 3 0 0 3 D/E
22MAT732 Categorical Data Analysis 3 0 0 3 D/E
22MAT733 Computational Biology 3 0 0 3 D/E
22MAT734 Computer aided drug designing 3 0 0 3 D/E
22MAT735 Demography and Actuarial Statistics 3 0 0 3 D/E
22MAT736 Healthcare  Analytics 3 0 0 3 D/E
22MAT737 Market Analytics 3 0 0 3 D/E
22MAT738 Mining of Massive Datasets 3 0 0 3 D/E
22MAT739 Official Statistics 3 0 0 3 D/E
22MAT740 Parallel and Distributed Systems 3 0 0 3 D/E
22MAT741 Pattern Recognition 3 0 0 3 D/E
22MAT742 Queuing Theory 3 0 0 3 D/E
22MAT743 Reinforcement Learning 3 0 0 3 D/E
22MAT744 Sampling Techniques 3 0 0 3 D/E
22MAT745 Social Network Analytics 3 0 0 3 D/E
22MAT746 Special Distribution Functions 3 0 0 3 D/E
22MAT747 Stochastic Process 3 0 0 3 D/E
22MAT748 Survival Analysis 3 0 0 3 D/E
22MAT749 Taugchi Techniques 3 0 0 3 D/E
22MAT750 Thanking with Data 3 0 0 3 D/E
Open Electives (PG)
Course Code Course Title L T P Cr. ES
21OEL631 Advanced Statistical Analysis for Research 2 0 0 2 D/E
21OEL632 Basics of PC Software 2 0 0 2 D/E
21OEL633 Computer Hardware and Networking 1 0 1 2 D/E
21OEL634 Consumer Protection Act 2 0 0 2 D/E
21OEL635 Corporate Communication 2 0 0 2 D/E
21OEL636 Design Studies 2 0 0 2 D/E
21OEL637 Disaster Management 2 0 0 2 D/E
21OEL638 Essentials of Cultural Studies 2 0 0 2 D/E
21OEL639 Foundations of Mathematics 2 0 0 2 D/E
21OEL640 Foundations of Quantum Mechanics 2 0 0 2 D/E
21OEL641 Glimpses of Life through Literature 2 0 0 2 D/E
21OEL642 Information Technology in Banking 2 0 0 2 D/E
21OEL643 Knowledge Management 2 0 0 2 D/E
21OEL644 Marketing Research 2 0 0 2 D/E
21OEL645 Media for Social Change 2 0 0 2 D/E
21OEL646 Media Management 2 0 0 2 D/E
21OEL647 Object-Oriented Programming 2 0 0 2 D/E
21OEL648 Painting and Sculpture 1 0 1 2 D/E
21OEL649 Personal Finance 2 0 0 2 D/E
21OEL650 Principles of Advertising 2 0 0 2 D/E
21OEL651 Principles of Packaging 2 0 0 2 D/E
21OEL652 Scripting for Rural Broadcasting 1 0 1 2 D/E
21OEL653 Social Media Website Awareness 1 0 1 2 D/E
21OEL654 Theatre Studies 1 0 1 2 D/E
21OEL655 Writing for Technical Purposes 2 0 0 2 D/E
21OEL656 Yoga and Personal Development 1 0 1 2 D/E
21OEL657 Fundamentals of Legal Awareness 2 0 0 2 D/E

Program Overview

Salient Features of the Program
  • Gain knowledge in computer programming and statistical software related to Applied Statistics and Data Analytics.
  • Placements in both conventional and software Industries.
  • Scope for doing research for those who aim to be a teacher, scientist or research associate in highly reputed national and international institutions.
  • Gain competency in the preparation of national level scholarship tests such as UGC/CSIR – NET and GATE.
About the curriculum and syllabi

The curriculum and syllabi for this program are on par with any reputed educational institution in India and abroad. Syllabus is framed in such a way that the candidates will be competent enough to take up the tests like NET, SLET, GATE etc. The Program offers comprehensive instruction in the theory, methods and application of Statistics. The courses include computer-intensive classes as a tool to support the analysis and interpretation of statistical data.

Job opportunities

Employment opportunities for people qualified with M.Sc. in Applied Statistics and Data analytics are available in the form of teaching positions in various educational institutions all over India and abroad. They are also eligible to work as Scientists and Research Associates in highly reputed organizations such as ISRO, DRDO and CSIR. In addition, lucrative jobs are available in software industries. In our integrated mathematics batch, while some of the students have got jobs in both public and private sector banks, many current final year students have already secured internships/jobs in industries (manufacturing/ software/insurance). The prospective recruiters for the students of Applied Statistics and Data Analytics are:

Current Students’ Feedback

The department always focuses on evolving with the changing needs of our stakeholders (students/parents/recruiters). The feedback from our stakeholders reveals that the curriculum and syllabi for Applied Statistics and Data Analytics are on par with any reputed educational institution in India and abroad. Students are finding it more interesting as the program is a combination of both Statistics and Data Analytics. They learn advanced programming languages and application of statistical software which are useful in industries and IT companies. The intersection of Statistics and Data Analytics has enabled more sophisticated ways in learning. They have learnt to implement, and do experiments with data analysis techniques and algorithms which will lead them to be effective practitioners in data handling at the end of second year. Students can identify and deploy appropriate modeling and methodologies in order to extract meaningful information for decision making. They can also analyze big data and make data-driven predictions through probabilistic modeling and statistical inference.

Program Outcomes
  • Knowledge in Statistics and Data Analytics: Understand the basic concepts, fundamental principles and the scientific theories related to Statistics and Data Analytics.
  • Abstract thinking: Ability to absorb and understand the abstract concepts that lead to various advanced theories in mathematics and Statistics.
  • Modelling and solving: Ability in modelling and solving problems by identifying and employing the appropriate existing theories and methods.
  • Advanced theories and methods: Understand advanced theories and methods to design solutions for complex statistical problems in Data Science.
  • Applications in Engineering and Sciences: Understand the role of statistics and apply the same to solve the real life problems in various fields of study.
  • Modern software tool usage: Acquire the skills in handling scientific tools towards problem solving and solution analysis in Data Science.
  • Environment and sustainability: Understand the significance of preserving the environment towards sustainable development.
  • 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 applied statistics and data analytics for constructive activities and demonstrate highest standards of professional ethics.
  • Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  • Communication: Develop various communication skills such as reading, listening, and speaking which will help in expressing ideas and views clearly and effectively.
  • Project management and Research: 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 analyse and solve advanced problems in data sciences.
  • 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.

Fee Structure



Proposed fee struture for Academic year 2024-2025
Sanctioned intake Proposed fee Caustion deposit Scholarship criteria
40  120000  10000 Not applicable
Program Fee for the year 2024-25(Semester Wise)
  • Tuition Fee: Rs. 44,600
  • Caution Deposit: Rs. 3,000

# Scholarship available for meritorious students. Please contact Admission Office (+91 830 400 4400) for details.

Refund Policy

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