Location: Mumbai
School: School of Management and Labour Studies
Intake: 30
Eligibility
Eligibility
Description
Selected_for_EPGDA-_2020-21.pdf
IMPORTANT DATES
Last Date for applying online |
to be announced shortly |
Personal Interview |
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Announcement of Selection on TISS Website |
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Last date for making the payment of fees |
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Commencement of Programme |
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Introduction
The convergence of information and communication technologies, deep learning and artificial intelligence is an exciting opportunity to organise complex systems and enhance our knowledge with new variants such as big data analytics and data science. Along with higher precision it also generates career opportunities in the labour market. Analytics, as a branch is not novel. We have spent considerable time and resources in designing, tabulating, presenting, drawing inferences, and predicting. The newer world, an information centric one, however, demands tools for handling bigger data sets that often cannot be handled by conventional statistical and econometric techniques such as regression.
Big data analytics differs from the conventional approach on three fronts;
Multi-lateral institutions like European Commission (EC) predicts a surge in Big Data/Data Science/Analytics professions in United Kingdom. As a pioneer in Information Technology, India is set to become an important node in the Big Data/ Data Science/Analytics global network. Tata Institute of Social Sciences (TISS), a public funded deemed university, offers an inclusive learning opportunity in Analytics. Labour Market Research Facility (LMRF) at TISS shall be anchoring the programme.
Executive Post Graduate Diploma in Analytics (EPGDA): Programme Design
Objectives of EPGDA
Key features of the programme
Distribution of Credit Hours:
Modules and Credits
The programme is of 1year duration with 690 hours of learning that is equivalent to 46 credits (Table 1). EPGDA is spread across 2 semester : Foundations, Technology and Applications, and Project Management.
Table 1: EPGDA Modules and Credits
Sr. No. | Semester | Credits |
Semester I | ||
1 | Data Structures and Research Designs: Cross Sectional, Time Series, Longitudinal, Excel Advanced and Visual Basics | 2 |
2 | Descriptive Statistics : Tabulation, Presentation and Visualization Using Tableau | 2 |
3 | Probability and Inferential Statistics | 4 |
4 | Multivariate Methods: Models and Methods | 2 |
5 | Data Science | 2 |
6 | Data Analysis with R | 4 |
7 | Data Analysis with Python | 4 |
8 | Data Analysis with SPSS | 2 |
Total Credits in Semester I | 22 | |
Semester II | ||
9 | Basics of Geographic Information System (GIS) | 2 |
10 | Introduction to Hadoop and cloud computing | 2 |
11 | Contemporary issues in Data Analytics(Non evaluative: Compulsory) | 2 |
12 |
Project Management |
2 |
13 | Analytics Projects in Business: Marketing, Human Resources Management, Finance, Strategy | 4 |
14 | Analytics Projects in Socio-Economic Planning: Social Protection/Poverty/Environment/Labour Market/Livelihoods/Health/Education | 4 |
15 | Analytics Projects in Social Media | 4 |
16 | Student Seminar on Analytics | 4 |
Total Credits in Semester II | 24 |
Semesterwise Courses:
LEARNING OUTCOMES FROM FOUNDATION COURSES:
Participants will be exposed to handling large social media data and large socio-economic databases such as National Sample Survey, National Family Health Survey, India Human Development Survey Data, Annual Survey of Industries, Economic Census, Census and longitudinal corporate databases. Quite important, in order to learn the basics of predictive analytics, participants will be exposed to probability and inferential processes and multivariate techniques. By the end of this module, participants will have learnt how to handle the data in terms of design, structure, presentation, inferences, and prediction.
SKILL DEVELOPMENT FROM TECHNOLOGY AND APPLICATIONS BASED COURSES :
Participants will learn technologies like R software, Python, Hadoop, Relational Databases, SPSS and GIS. Participants will get opportunity to innovate creative data/technology integration processes.
PRACTICAL EXPERIENCE FROM PROJECT MANAGEMENT AND DESERTATION :
Participants will learn behavioural, financial, and technical nuances of project management in terms of people skill, scheduling, documentation, presentation, and so on. Participants will work on analytics projects in diverse domains such as marketing, human resources, finance, strategy, labour market, livelihood, health, poverty, environment, education, and social media.
Pedagogy and Evaluation
The programme will use an interactive and integrative pedagogy, consisting of lectures, live projects, practicum, seminar, and case studies. TISS evaluation standards will be applicable to EPGDA.
Fee Structure:
Sr. No. | Particulars | Installment 1 | Installment 2 |
During Admission | 10th August, 2020 | ||
1 | Tuition | 1,19,100 | 1,16,600 |
2 | Identity Card | 300 | -- |
3 | Examination | 1000 | 1000 |
4 | Computer Infrastucture | 1000 | 1000 |
5 | Development Fund | 2500 | 2500 |
6 | Library | 1000 | -- |
7 | Library Deposit (Refundable) | 2000 | -- |
8 | Convocation Charges | -- | 2000 |
Total | 1,26,900 | 1,23,100 | |
Grand Total | 2,50,000 |
CLASS TIMINGS
Saturdays : 2:00 pm to 8:00 pm
Sundays : 9:00 am to 4:00 pm
The classes will be held at the Institute
premises (Mumbai Campus) every weekend
SUPPORT
Candidates facing technical issues are requested to write an email to pgadmission@tiss.edu /analyticstiss@gmail.com with an appropriate subject and description of the problem. Alternatively the candidate can call TISS Helpline 022-25525252 for general enquiries or for registering technical issues faced while filling the online application form.
SELECTION PROCEDURE
Those satisfying the eligibility requirement will be called for the Personal Interview by the Selection Committee. The list of selected candidates will be notified on the Institute Website (http://www.tiss.edu). The Institute will not take responsibility for informing the selected candidates by post.
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