M.Sc. in Applied Statistics and Data Analytics (Offered at Coimbatore Campus)

Overview

Students who want to excel at data analytics should enroll in the two-year M.Sc. programme in Applied Statistics and Data Analytics. It offers a range of fundamental to sophisticated statistical techniques and their applications to both traditional and IT businesses, allowing for the solution of new issues. 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 curriculum includes cutting-edge topics like big data analytics, pattern recognition, and marketing analytics. Students are encouraged to enroll in an internship or in-plant training programme over the summer or winter in addition to their regular coursework.

This will assist students in learning how to use data mining techniques to analyse data, find patterns, and suggest analytical models to identify and address various patterns such as structural patterns, creational patterns, and behavioral patterns. By incorporating the analytical models into the consistent operational applications, these models will then enhance the implementation of business, technological, industrial, and healthcare processes. The programme includes a substantial project that must be finished in the last semester. Such tasks in the workplace are required of students. Students can learn about workplace circumstances and requirements for the workforce from doing this.

Programme Duration: 2 years (4 Semesters)

Dates to note

08 Feb

Commencement of Application form (kochi)

Curriculum

Semester 1 Semester 2 Semester 3 Semester IV Electives (any three) Open Electives (PG)

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.

Hostel & Mess Fee for the year 2022-23
CAMPUS	Caution Deposit (ONE TIME)	HOSTEL FEE PER YEAR	MESS FEE PER YEAR
Coimbatore	10,000	52,000	56,000

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Overview

Dates to note

Important Note

Commencement of Application form (kochi) : February 08th ,2023

Curriculum

Admission

Eligibility

Admission process

Program Overview

Year-wise Curriculum & Syllabus

Fee Structure

Fee Structure (Semester Wise)

Scholarship Fees

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