Department of Mathematics offers Five-Year Integrated MSc Program in Data Science and this Program covers topics in computer science along with mathematics and statistics so that students will be able to analyze, contextualize, and draw insights from the data. The program offers strong preparation in statistical modeling, machine learning, optimization, management and analysis of massive data sets, and data acquisition. This program helps students to become Data Scientists and also prepares them for pursuing higher studies. In order to deal with vast amount of data sets generated by businesses, healthcare, sensors, the Internet, surveys, social media, astronomy, human space exploration and operations, and aeronautics, the curriculum includes cutting-edge topics such as Big Data Analytics, Machine Learning, Neural Networks, Pattern Recognition, Data Visualization, and Data Modeling and Business Analytics. Students are encouraged to enroll in internships or in-plant training programs during the summer and/or winter vacations. In fact, the Program is designed to blend the skills in mathematics and statistics with the advent of computing facility in providing solutions to the challenging problems of aforementioned domains.
The curriculum is so designed to enable students to explore opportunities for internship in their Ninth semester. Further, a substantial opportunity is given to the students for independent study and research in the form of a mini project in eighth semester and a project work transforming it into Dissertation. This project work will typically involve literature survey, investigation and their contribution over a particular area of Mathematical Sciences. This dissertation will result in a research article for publication in a reputed journal and is strongly believed to help aspirants planning for PhD.
The students exchange program is another vital feature that helps students who wish to explore the possibilities of higher studies in top Universities of USA and Europe countries.
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.
Please review admissions requirements and other information before applying. You can find degree program-specific admissions requirements in website on applying from the Department of Mathematics.
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 minimum of aggregate 50% marks in Physics, Chemistry, and Mathematics in +2 examination
Selection for the undergraduate program is based on a thorough evaluation of candidates’ performance in their Plus Two examinations.
The above policy will be valid, only if there is any new directive from the UGC on the Last date of admission.
| Course Code | Course Title | L | T | P | Cr |
| 21ENG101 | Communicative English | 2 | 0 | 2 | 3 |
| Language Paper I | 1 | 0 | 2 | 2 | |
| 22MAT108 | Calculus | 3 | 1 | 0 | 4 |
| 22MAT109 | Linear Algebra | 3 | 0 | 2 | 4 |
| 22PHY101 | Physics | 3 | 0 | 0 | 3 |
| 22CSC101 | Problem Solving and Computer Programming | 3 | 0 | 0 | 3 |
| 22CSC181 | Problem solving computer Lab | 0 | 0 | 2 | 1 |
| 22PHY181 | Physics Lab | 0 | 0 | 2 | 1 |
| 21CUL101 | Cultural Education I | 2 | 0 | 0 | 2 |
| Total | 23 |
| Course Code | Course Title | L | T | P | Cr |
| 21ENG111 | Professional Communication | 1 | 0 | 2 | 2 |
| Language Paper II | 1 | 0 | 2 | 2 | |
| 22MAT118 | Vector Calculus | 3 | 1 | 0 | 4 |
| 22MAT119 | Discrete Mathematics | 3 | 0 | 2 | 4 |
| 22CSC111 | Advanced Computer Programming | 3 | 0 | 0 | 3 |
| 22CSC112 | Digital Electronics | 3 | 0 | 0 | 3 |
| 22CSC182 | Advanced Computer Programming Lab. | 0 | 0 | 2 | 1 |
| 22CSC183 | Digital Electronics Lab | 0 | 0 | 2 | 1 |
| 21CUL111 | Cultural Education II | 2 | 0 | 0 | 2 |
| 22AVP103 | Mastery Over Mind | 1 | 0 | 2 | 2 |
| TOTAL | 24 |
| Course Code | Course Title | L | T | P | Cr |
| 22CSC201 | Data Structures | 3 | 1 | 0 | 4 |
| 22MAT224 | Optimization Techniques | 3 | 1 | 0 | 4 |
| 22MAT225 | Probability Theory | 3 | 1 | 0 | 4 |
| 22MAT226 | Numerical Methods | 3 | 1 | 0 | 4 |
| 22CSC202 | Foundations of Data Science | 3 | 0 | 2 | 4 |
| 19ENV300 | Environmental Science | P/F | |||
| 22MAT286 | Data Science Lab-I: Statistics and Numerical Methods Lab | 0 | 0 | 2 | 1 |
| 21AVP201 | Amrita Values Programme I | 1 | 0 | 0 | 1 |
| 22CSC281 | Data Structures lab | 0 | 0 | 2 | 1 |
| 21SSK201 | Life Skills I | 1 | 0 | 2 | 2 |
| TOTAL | 25 |
| Course Code | Course Title | L | T | P | Cr |
| 22MAT227 | Statistical Inference Theory | 3 | 0 | 0 | 3 |
| 22MAT228 | Introduction to Modern Algebra | 3 | 0 | 0 | 3 |
| 22MAT229 | Convex Optimization | 3 | 0 | 0 | 3 |
| 22CSC211 | Design and Analysis of Algorithms | 3 | 1 | 0 | 4 |
| 22CSC212 | Database Management Systems | 3 | 1 | 0 | 4 |
| Open Elective A* | 3 | 0 | 0 | 3 | |
| 22MAT287 | Data Science Lab-II: Inference Theory | 0 | 0 | 2 | 1 |
| 21SSK211 | Life Skills II | 1 | 0 | 2 | 2 |
| 22CSC282 | Design and Analysis of Algorithms Lab | 0 | 0 | 2 | 1 |
| 21AVP211 | Amrita Values Programme II | 1 | 0 | 0 | 1 |
| TOTAL | 25 |
| Course Code | Course Title | L | T | P | Cr |
| 22CSC301 | Operating Systems | 3 | 0 | 2 | 4 |
| 22MAT310 | Multivariate Statistics for Data Science | 3 | 0 | 2 | 4 |
| 22CSC302 | Number Theory and Information Security | 3 | 1 | 0 | 4 |
| 22CSC303 | Theory of Computation | 3 | 0 | 2 | 4 |
| 22CSC304 | Database Design | 3 | 0 | 0 | 3 |
| 22MAT392@ | Live-in-Lab.@ / Open Elective B* | 3 | 0 | 0 | 3 |
| 21SSK301 | Life Skills III | 1 | 0 | 2 | 2 |
| 22CSC381 | Database Management Systems Lab | 0 | 0 | 2 | 1 |
| TOTAL | 25 |
| Course Code | Course Title | L | T | P | Cr |
| 22MAT321 | Graph Analytics and Algorithms | 3 | 0 | 2 | 4 |
| 22MAT322 | Regression Analysis | 3 | 0 | 2 | 4 |
| 22CSC311 | Machine Learning | 3 | 1 | 0 | 4 |
| 22CSC312 | Data Visualization | 3 | 0 | 2 | 4 |
| 22CSC313 | Computer Networks | 3 | 0 | 2 | 4 |
| 22CSC314 | Data Governance, Ethics and Law | 1 | 0 | 0 | 1 |
| 22CSC382 | Machine Learning-Lab | 0 | 0 | 2 | 1 |
| 22CSC383 | Open Lab I (JAVA / C / C++ / R programming / Azure …) | 0 | 0 | 2 | 1 |
| TOTAL | 23 |
| Course Code | Course Title | L | T | P | Cr |
| 22MAT401 | Probabilistic Graphical Models for Data Science | 3 | 0 | 2 | 4 |
| 22CSC401 | Deep Learning | 3 | 0 | 2 | 4 |
| 22CSC402 | Practical Techniques for Big Data Analytics | 3 | 0 | 2 | 4 |
| 22CSC403 | Reinforcement Learning | 3 | 0 | 2 | 4 |
| 22CSC404 | Data Security | 3 | 0 | 0 | 3 |
| Elective I | 2 | 0 | 2 | 3 | |
| Elective II | 2 | 0 | 2 | 3 | |
| 22CSC481 | Open Lab-II (Algorithms.io / Hadoop / Cascading / web design./ RapidMiner.,/ Research paper) | 0 | 0 | 2 | 1 |
| TOTAL | 26 |
| Course Code | Course Title | L | T | P | Cr |
| 22CSC411 | Software Engineering | 3 | 0 | 2 | 4 |
| 22CSC412 | Deep Learning for Natural Language Processing | 3 | 0 | 2 | 4 |
| Elective III | 2 | 0 | 2 | 3 | |
| Elective IV | 2 | 0 | 2 | 3 | |
| Elective V | 2 | 0 | 2 | 3 | |
| 22CSC490 | Mini Project | 5 | |||
| 22CSC413 | Internet of Things | 1 | 0 | 2 | 2 |
| 22CSC482 | Open Lab-III (Apache Spark / Big ML /Apache Hive/ Research paper/…) | 0 | 0 | 2 | 1 |
| TOTAL | 25 |
| Course Code | Course Title | L | T | P | Cr |
| 22CSC691 | Project –I(Internship in Industries / Universities) | 8 | |||
| Elective VI | 2 | 0 | 2 | 3 | |
| Elective VII | 2 | 0 | 2 | 3 | |
| Total | 14 |
| Course Code | Course Title | L | T | P | Cr |
| 22CSC699 | Project-II (Research based) Dissertation | 12 | |||
| TOTAL | 12 | ||||
| Total Credits | 222 |
| Course Code | Course Title | L | T | P | Cr |
| 22MAT431 | Real Analysis | 2 | 0 | 2 | 3 |
| 22MAT432 | Advanced Algebra | 2 | 0 | 2 | 3 |
| 22MAT433 | Transform Techniques | 2 | 0 | 2 | 3 |
| 22MAT434 | Advanced Big Data Analytics | 2 | 0 | 2 | 3 |
| 22MAT435 | Differential Equations | 2 | 0 | 2 | 3 |
| 22MAT436 | Random Process for Data Analytics | 2 | 0 | 2 | 3 |
| 22MAT437 | Time Series Analysis | 2 | 0 | 2 | 3 |
| 22MAT438 | Wavelets | 2 | 0 | 2 | 3 |
| 22MAT439 | Computational Geometry | 2 | 0 | 2 | 3 |
| 22MAT440 | Queuing Theory and Inventory Control | 2 | 0 | 2 | 3 |
| 22MAT441 | Theory of Sampling and Design of Experiments for Data Analysis | 2 | 0 | 2 | 3 |
| 22MAT442 | Data Analytics in Computational Biology | 2 | 0 | 2 | 3 |
| 22MAT443 | Computer Aided Drug Designing | 2 | 0 | 2 | 3 |
| 22MAT444 | Statistical Quality Control | 2 | 0 | 2 | 3 |
| 22MAT445 | Six Sigma Analytics | 2 | 0 | 2 | 3 |
| 22MAT446 | Statistical Pattern Recognition | 2 | 0 | 2 | 3 |
| Course Code | Course Title | L | T | P | Cr |
| 22CSC541 | Soft Computing | 2 | 0 | 2 | 3 |
| 22CSC542 | Cryptography | 2 | 0 | 2 | 3 |
| 22CSC543 | Business Analytics | 2 | 0 | 2 | 3 |
| 22CSC544 | Deep Learning for Image Processing | 2 | 0 | 2 | 3 |
| 22CSC545 | Predictive Analytics | 2 | 0 | 2 | 3 |
| 22CSC546 | Mining of Massive Datasets | 2 | 0 | 2 | 3 |
| 22CSC547 | Data Compression | 2 | 0 | 2 | 3 |
| 22CSC548 | Introduction to Embedded Systems | 2 | 0 | 2 | 3 |
| 22CSC549 | Information retrieval | 2 | 0 | 2 | 3 |
| 22CSC550 | Social Network Analytics | 2 | 0 | 2 | 3 |
| 22CSC551 | Big Data Storage and Analysis | 2 | 0 | 2 | 3 |
| 22CSC552 | Full Stack Development | 2 | 0 | 2 | 3 |
| 22CSC553 | Cloud Computing | 2 | 0 | 2 | 3 |
| 22CSC554 | Data Wrangling | 2 | 0 | 2 | 3 |
| 22CSC555 | Parallel and Distributed Systems | 2 | 0 | 2 | 3 |
| 22CSC556 | High Performance Computing | 2 | 0 | 2 | 3 |
| 22CSC557 | Advance Deep Learning | 2 | 0 | 2 | 3 |
Elective courses can be taken from online courses, industry electives and other B.Tech / M.Tech/ M. Sc programmes.
@ code for live in Lab
| Course Code | Course Title | L | T | P | Cr | ES | Course Code | Course Title | L | T | P | Cr | ES |
| Paper I | Paper II | ||||||||||||
| 21HIN101 | Hindi I | 1 | 0 | 2 | 2 | B | 21HIN111 | Hindi II | 1 | 0 | 2 | 2 | B |
| 21TAM101 | Tamil I | 1 | 0 | 2 | 2 | B | 21TAM 111 | Tamil II | 1 | 0 | 2 | 2 | B |
| 21KAN101 | Kannada I | 1 | 0 | 2 | 2 | B | 21KAN111 | Kannada II | 1 | 0 | 2 | 2 | B |
| 21MAL101 | Malayalam I | 1 | 0 | 2 | 2 | B | 21MAL111 | Malayalam II | 1 | 0 | 2 | 2 | B |
| 21SAN101 | Sanskrit I | 1 | 0 | 2 | 2 | B | 21SAN111 | Sanskrit II | 1 | 0 | 2 | 2 | B |
| Course Code | Course Title | L | T | P | Cr | |
| Course Code | Course Title | L | T | P | Cr. | ES |
| 21OEL231 | A Journey towards Free India | 3 | 0 | 0 | 3 | J |
| 21OEL232 | Political Leadership | 3 | 0 | 0 | 3 | J |
| 21OEL233 | Social issues in Contemporary India | 3 | 0 | 0 | 3 | J |
| 21OEL234 | The Story of Indian Business | 3 | 0 | 0 | 3 | J |
| 21OEL235 | Industrial Psychology | 3 | 0 | 0 | 3 | J |
| 21OEL236 | Advertising | 3 | 0 | 0 | 3 | J |
| 21OEL237 | Basic Statistics | 3 | 0 | 0 | 3 | J |
| 21OEL238 | Citizen Journalism | 3 | 0 | 0 | 3 | J |
| 21OEL239 | Creative Writing for Beginners | 3 | 0 | 0 | 3 | J |
| 21OEL240 | Desktop Support and Services | 3 | 0 | 0 | 3 | J |
| 21OEL241 | Development Journalism | 3 | 0 | 0 | 3 | J |
| 21OEL242 | Digital Photography | 3 | 0 | 0 | 3 | J |
| 21OEL243 | Emotional Intelligence | 3 | 0 | 0 | 3 | J |
| 21OEL244 | Essence of Spiritual Literature | 3 | 0 | 0 | 3 | J |
| 21OEL245 | Film Theory | 3 | 0 | 0 | 3 | J |
| 21OEL246 | Fundamentals of Network Administration | 3 | 0 | 0 | 3 | J |
| 21OEL247 | Gender Studies | 3 | 0 | 0 | 3 | J |
| 21OEL248 | Glimpses of Indian Economy and Polity | 3 | 0 | 0 | 3 | J |
| 21OEL249 | Graphics and Web-designing Tools | 3 | 0 | 0 | 3 | J |
| 21OEL250 | Green Marketing | 3 | 0 | 0 | 3 | J |
| 21OEL251 | Healthcare and Technology | 3 | 0 | 0 | 3 | J |
| 21OEL252 | History of English Literature | 3 | 0 | 0 | 3 | J |
| 21OEL253 | Indian Writing in English | 3 | 0 | 0 | 3 | J |
| 21OEL254 | Industrial Relations and Labour Welfare | 3 | 0 | 0 | 3 | J |
| 21OEL255 | Introduction to Ancient Indian Yogic and Vedic Wisdom | 3 | 0 | 0 | 3 | J |
| 21OEL256 | Introduction to Computer Hardware | 3 | 0 | 0 | 3 | J |
| 21OEL257 | Introduction to Event Management | 3 | 0 | 0 | 3 | J |
| 21OEL258 | Introduction to Media | 3 | 0 | 0 | 3 | J |
| 21OEL259 | Introduction to Right to Information Act | 3 | 0 | 0 | 3 | J |
| 21OEL260 | Introduction to Translation | 3 | 0 | 0 | 3 | J |
| 21OEL261 | Linguistic Abilities | 3 | 0 | 0 | 3 | J |
| 21OEL262 | Literary Criticism and Theory | 3 | 0 | 0 | 3 | J |
| 21OEL263 | Macro Economics | 3 | 0 | 0 | 3 | J |
| 21OEL264 | Managing Failure | 3 | 0 | 0 | 3 | J |
| 21OEL265 | Media Management | 3 | 0 | 0 | 3 | J |
| 21OEL266 | Micro Economics | 3 | 0 | 0 | 3 | J |
| 21OEL267 | Micro Finance, Small Group Management and Cooperatives | 3 | 0 | 0 | 3 | J |
| 21OEL268 | Negotiation and Counselling | 3 | 0 | 0 | 3 | J |
| 21OEL269 | New Literatures | 3 | 0 | 0 | 3 | J |
| 21OEL270 | Non-Profit Organization | 3 | 0 | 0 | 3 | J |
| 21OEL271 | Personal Effectiveness | 3 | 0 | 0 | 3 | J |
| 21OEL272 | Perspectives in Astrophysics and Cosmology | 3 | 0 | 0 | 3 | J |
| 21OEL273 | Principles of Marketing | 3 | 0 | 0 | 3 | J |
| 21OEL274 | Principles of Public Relations | 3 | 0 | 0 | 3 | J |
| 21OEL275 | Science, Society and Culture | 3 | 0 | 0 | 3 | J |
| 21OEL276 | Statistical Analysis | 3 | 0 | 0 | 3 | J |
| 21OEL277 | Teamwork and Collaboration | 3 | 0 | 0 | 3 | J |
| 21OEL278 | The Message of Bhagwad Gita | 3 | 0 | 0 | 3 | J |
| 21OEL279 | Understanding Travel and Tourism | 3 | 0 | 0 | 3 | J |
| 21OEL280 | Videography | 3 | 0 | 0 | 3 | J |
| 21OEL281 | Vistas of English Literature | 3 | 0 | 0 | 3 | J |
| 21OEL282 | Web-Designing Techniques | 3 | 0 | 0 | 3 | J |
| 21OEL283 | Organic Farming | 3 | 0 | 0 | 3 | J |
| 21OEL284 | Basic Legal Awareness on Protection of Women and Rights | 3 | 0 | 0 | 3 | J |
| 21OEL285 | Ritual Performances of Kerala | 3 | 0 | 0 | 3 | J |
| 21OEL286 | Documenting Social Issues | 3 | 0 | 0 | 3 | J |
| 21OEL287 | Fabrication of Advanced Solar Cell | 3 | 0 | 0 | 3 | J |
| 21OEL288 | Basic Concepts of X-ray Diffraction | 3 | 0 | 0 | 3 | J |
| 21OEL289 | Introduction to FORTRAN and GNUPLOT | 3 | 0 | 0 | 3 | J |
| 21OEL290 | Introduction to Porous Materials | 3 | 0 | 0 | 3 | J |
| 21OEL291 | Forensic Science | 3 | 0 | 0 | 3 | J |
| 21OEL292 | Introduction to solar Physics | 3 | 0 | 0 | 3 | J |
| 21OEL293 | Recycling Recovery and Treatment Methods for Wastes | 3 | 0 | 0 | 3 | J |
| 21OEL294 | Acting and Dramatic Presentation | 2 | 0 | 2 | 3 | J |
| 21OEL295 | Computerized Accounting | 2 | 0 | 2 | 3 | J |
| 21OEL296 | Kerala Mural Art and Painting | 2 | 0 | 2 | 3 | J |
| 21OEL297 | Painting | 2 | 0 | 2 | 3 | J |
| 21OEL298 | Reporting Rural Issues | 3 | 0 | 0 | 3 | J |
In addition to the regular curriculum, students are encouraged to take up summer/winter In-plant training/Internship. This will help students to gain real time processing of data by doing Prediction analysis, Pattern Recognition, Anomaly Detection, Clustering, Actionable Insights, Automated Processes and decision making, Segmentation, Optimization and Forecasting. A full length project is included in the curriculum to be completed in the final semester. Students are expected to take up such projects in industries. This helps students to gain knowledge on working conditions and industrial requirements when they are employed.
Harvard was right about data scientists. It’s an extremely important and high-demand role that can have significant impact on a business’ ability to achieve its goals, whether they are financial, operational, strategic, and so on.
Data Science curriculum is carefully designed to cater the industrial needs and it includes Mathematics, Computer Science and Business Analytics. The syllabus starts with the basics in Calculus, Mathematical Logic, Probability, Statistics, Linear Algebra, Data Management and Analytics to advanced topics like Neural Networks, Artificial Intelligence, Machine Learning, Data Modeling and Big Data.
Employment opportunities for students with Data Science degree are plenty in the job market. The need for Data Scientists is growing every day in all fields. Harvard calls the Data Scientist job as the Sexiest job of 21st Century. 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. The prospective recruiters for the students of Integrated Data Science are:
| Fee Structure 2025 – 2026 | |||
| Name of the programme | Duration (Year) | Intake | Fee structure( per annum) |
|---|---|---|---|
| Integrated M.Sc. Data Science | 5 | 120 | 225000 |
| Hostel & Mess Fee Details 2025-26 | |||||
| Course | Gender | Hostel Fee (Rs.) | Mess Fee (Rs.) | Caution Deposit (Rs.) | Total (Rs.) |
| UG (B.Sc / Integrated) | Girls | 52,000 | 60,000 | 10,000 | 1,22,000 |
| UG (B.Sc / Integrated) | Boys | 60,000 | 60,000 | 10,000 | 1,30,000 |
The top reasons to choose Amrita for your career
Chairman Admissions
Amrita Vishwa Vidyapeetham
Amritanagar Post, Ettimadai,
Coimbatore – 641 112
Tamil Nadu, India
For Enquiries Call :
9943984591,
9943984444
admissionasas@cb.amrita.edu
Toll-free Number: 044-401-16055
Phone : 0422 2685321
