School: School of Management and Labour Studies
( 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 Data2. Grounded Learning on the Philosophy of Analytics and Predictive Modelling 3. Applying the analytics to the Sustainable Development Goal (SDG) contexts4. Collaborative Live Analytics projects with Industry and Civil Society Organisations5. Bench-marking with Global Learning Standards in Analytics 6. Modelling the Economy, Business, Organisations, Society, and Environment7. Transforming Ideas into Data Products8. Human Dimension of Data and Technologies9. Interactive Learning through regular series of seminars and workshops
Distribution of Credit Hours:
Choice Based Credit Courses (Displinary Electives)
Overview of Courses and Credits
Mathematics for Analytics
Statistics for Analytics
Introduction to Tools for Data Analysis & Visualization
Workshop on Data Ethics
Compulsory and Non-Evaluative
Data Science & Database Management
Multivariate Predictive Analysis I
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)
Financial Econometrics Disciplinary Elective (2 out of 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.
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