PGDM 311017

PGDQF3110117

pgpsm final

CSL311017


Data Science and Big Data Analytics are exciting new areas that combine scientific inquiry, statistical knowledge, substantive expertise, and computer programming. One of the main challenges for businesses and policy makers when using big data is to find people with the appropriate skills. Good data science requires experts that combine substantive knowledge with data analytical skills, which makes it a prime area for social scientists with an interest in quantitative methods. This course integrates prior training in quantitative methods (statistics) and coding with substantive expertise and introduces the fundamental concepts and techniques of Data Science and Big Data Analytics.

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PGDDS 2017-18 Prospectus
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Post Graduate Diploma in Data Science is a nine month part-time programme aimed at creating the next generation Analyst and Data Scientist. For students interested in analytics, technology firms, regulators, consulting and universities across the globe. PGDDS is an extremely unique opportunity to obtain first-hand knowledge, both theoretical and practical, from NISM an institute established by SEBI, the market regulator and prestigious Department of Economics (Autonomous), University of Mumbai. The faculty, consisting of academicians and practitioners, has the capability to deliver a high-quality and cutting-edge programme to the students looking for knowledge and skill-sets as a solid foundation.

 

The 21stCentury Belongs to

                       Data Scientists

 

Where PGDDS can lead to?

Financial Analytics,
Data Analyst,
Marketing: Managers,
Market Research Analyst and Specialist,
Research Scientist.
& more

Programme Highlights

This course provides participants with:
• An understanding of the structure of datasets and databases, including "big data"
• The ability to work with datasets and databases
• An introduction to programming languages and basic skills in the R/ Python statistical program
• The ability to analyze data using statistical and machine learning methods.
• The ability to apply to analyze large financial data for decision making purpose

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