M.A. Admissions

Master of Arts/Master of Science(Analytics) (Self Financed)

Location: Mumbai

School: School of Management and Labour Studies

Intake: 34


( This is a Self Financed program, no fee concession or waivers available for this program. )


In the milieu of convergent information and communication technologies (ICT) and growing application of artificial intelligence, analytics of big data and data science generate exciting career opportunities in the labour market. For long people have been doing the analytics; they have been designing, tabulating, presenting, drawing inferences, and predicting. Varian (2014), however, view why the analytics turns out to be an exciting opportunity.

“Computers are now involved in many economic transactions and can capture data associated with these transactions, which can then be manipulated and analyzed. Conventional statistical and econometric techniques such as regression often work well but there are issues unique to big datasets that may require different tools”.

Moreover, Varian provides three reasons for why analytics of big data is distinct from conventional approaches: volume of data, more potential predictors, and large data sets unravel complex non-linear patterns. Ackermann and Angus (2014) provides examples of analytics applications to social sciences. Multi-lateral institutions like European Commission (EC) provides estimates of discernibly huge demand Big Data/Data Science/Analytics professions in United Kingdom. Not only this segment of labour is likely to grow exponentially, also occupational profiles in this sector may provide better reward packages than Information Technology (IT) and IT enabled services do offer. Tata Institute of Social Sciences (TISS), being a public funded deemed university, aspires to provide learners more inclusive opportunities in Analytics. In January 2018, the School has launched a short term learning progarmme for working professionals ‘Executive Post Graduate Diploma in Analytics (EPGDA)’. The first batch of EPGDA has graduated in January, 2019, second batch is on going, while the Third batch will begin from February 2020.

Since its inception, the programme has been coordinated by the Labour Market Research Facility at the School. The Labour Market Research Facility (LMRF) is a think tank that specialises in macro and micro labour market, household sample surveys, working and living condition surveys and macro labour market analysis. The think tank has won some of the prestigious global research grants, and has created exemplary capabilities in extraction and analysis of large sample databases such as National Sample Survey and Annual Survey of Industry. As an ecology of research, the LMRF continues to support M.Phil. and Ph.D. scholars who pursue research in labour-related themes.

While the current programme (EPGDA) caters to the learning needs of the working professionals, there appears to be space for envisaging a full-fledged post graduate programme in Analytics. The proposed Master of Arts (M.A.) or Master of Science (M.Sc) in Analytics will be distinct from the learning programmes in analytics offered by other institutions since this programme captures both policy analytics and technological aspects of the analytics.


Reasons to do an M.A in Analytics from TISS

1. Visualize and Analyse the Big Data
2. Grounded Learning on the Philosophy of Analytics and Predictive Modelling
3. Applying the analytics to the Sustainable Development Goal (SDG) contexts
4. Collaborative Live Analytics projects with Industry and Civil Society Organisations
5. Bench-marking with Global Learning Standards in Analytics
6. Modelling the Economy, Business, Organisations, Society, and Environment
7. Transforming Ideas into Data Products
8. Human Dimension of Data and Technologies
9. Interactive Learning through regular series of seminars and workshops

Distribution of Credit Hours:


Year Details Credits
First      Foundation Course 4
Core Courses 20
Dissertation Stage 1 2
Choice Based Credit System (Elective Foundation) 2
Choice Based Credit System (Open Elective) 2

Choice Based Credit Courses (Displinary Electives)

Second Core Courses 16
Dissertation Stage 2 & 3 8
Internship 6
Total Credits



Semesterwise Courses:



Overview of Courses and Credits


.Course code

Course Title




Foundation Course


A 01

Mathematics for Analytics


A 02

Statistics for Analytics

A 03

Introduction to Tools for Data Analysis & Visualization

A 04

Workshop on Data Ethics

Compulsory and Non-Evaluative 

A 05

Data Science & Database Management

A 06

Multivariate Predictive Analysis I

A 07

Introduction to GIS


Elective Foundation Course


Open Elective Course


CBCS Disciplinary Elective Courses (Any two from the pool of AO 8.1 to A 8.6)

  AO 8.1

Financial Econometrics Disciplinary Elective (2 out of 6)

 AO 8.2

Environmental Analytics

AO 8.3 HR Analytics 2
AO 8.4 Health Analytics 2
AO 8.5 Analytics in Sustainable Development 2
AO 8.6 Social Network and Media Analytics 2
ADS 01 Dissertation Stage I: Proposal 2
                 III A09 Internship (2 months) 6
A10 Multivariate Predictive Analysis II 4
A11 Bayesian Statics 2
A12 Economic Impact Evaluation 2
A13 Psychometrics 2
A14 Machine Learning 4
ADS 02 Dissertation Stage II : Review of Literature & Research Design 2
          IV A15 Python Programming for Analytics 2
ADS 03 Dissertation Stage III: Final Dissertation 6

 Note: The Total number of creditts, list of CBCS curses and semester- wise listing of courses is provisional, and may undergo some changes. Due to current pandemic situation courses may be shifted or taught across semesters.

Fee Structure:


Fees Sem I Sem II
Sem III Sem IV
FEE Tuition Fee 12000 12000 12000 12000
Examination Fee 800 800 800 800
Health Centre Charges 100 0 0 0

Field Work Charges 4000 4000 4000 4000
IT Charges 1000 1000 1000 1000
Convocation Charges 0 0 0 2000
ID Card Charges 300 0 0 0
FUNDS Students' Competency Fund     20000 0 0  
Internship Fund 0 0 0 0
Lab Charges / Studio Fund     20000 0 0 0
Dev. Fund / Prog. Fund 130000 130000 130000 130000
Students' Union Fund 500 500 500 500
Medical Insurance Fund 1500 0 1500 0
DEPOSITS & ADVANCES A)  Caution Deposits (Refundable at the time of exit from programme on submission of No Dues Certificate) 10000 0 0 0
B)  *Practicum / Study Tour Charges (Rural Field Work / Urban Field Work) (Refundable) 0 0 0 0
Dining Hall (Advance) Charges 16000 16000 16000 16000
OTHER CHARGES Hostel & Electricity Charges Rs.10000 & Rs.5000 15000 15000 15000 15000
Total Fees for Non-Hostellers 200200 148300 149800 150300
Total Fees for Hostellers 231200 179300 180800 181300
*Details under School
* "Practicum / Study tour charges / Rural Field Work / Urban Field Work charges are not part of the fee structure.  However, expenses will have to be met by the students at the time of study tour."

*Institute reserves the rights to revise the Fees Structure of programme if necessary.