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M.Phil. in Data Analytics & Cloud Computing

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M.Phil. in Data Analytics & Cloud Computing

(Evening Programme)

Eligibility : MCA, M.Tech. (CS/IT/EC), & M.Sc. (Maths/CS/Electronics, Stat,) Graduates any UGC recognized University with 50 % Marks

Duration : One year (3 Trimester Program)

About the Course :

M.Phil. in Data Analytics & Cloud Computing is a super specialization course designed to meet growing needs of expertise required in 21st century for IT Management. The course contents are designed to cope the essentials of fundamental knowledge and advanced skills required to an effective decision maker in big data handling environment. By keeping the entry level as any postgraduates in Computer Science & related subjects, the course contents spreading three trimesters with 12 core subjects and one master industry level project lifts the participants to advanced level as multi-disciplinary backed decision makers. This will add strength to their lateral thinking beyond the imagination while handling critical situations in IT industries & IT enables Services industry to make optimum decisions in global big data & cloud computing environment. The course is offered to working professionals during evening time with weekly three days contact based training and other three days self-study through online distributed software/assignment work. The course also facilitates the postgraduates who want to grow quickly through identifying and encashing attractive opportunities or accelerated promotions in their job with an objective and true sense of creating innovators.

Why Data Analytics :

Business Analytics also known as Business Intelligence (BI) has become strategically important for every organisation to keep competitive advantage by extracting meaningful information from the flood of digital data collected by businesses, government, and scientific agencies. The recent years have seen explosive growth of digital data stored in computer databases. With continued innovation revolving around digital technologies, the Internet and mobile computing, the amount of data continues to grow exponentially. At this rate, there will soon be a shortage of talented analysts who can help organisations work with this much big data. McKinsey Global Institute’s Big data: The next frontier for innovation, competition, and productivity estimates that by 2018, “the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions”. The earning opportunity through job & consultancy work for Business Analytics Experts is 5 to 10 times more than other professions in the society.

Course Structure :

S.No SUBJECT Marks Study Hours
TRIMESTER 1
1 Programming using Python (T&P) 100 40
2 R – Programming Fundamentals (T&P) 100 40
3 Data warehousing and Data Mining (T & P) 100 40
4 Big Data technologies 100 40
5 Database Systems in Big Data (T & P) 100 40
6 Mini Project 100 40
TRIMESTER 2
1 Hadoop Distributed File Systems (T & P) 100 40
2 Map Reduce (T & P) 100 40
3 Big Data Analytics (T & P) 100 40
4 Data Mining Application with R (T & P) 100 40
5 Marketing & Social Media Analytics 100 40
6 Empirical Research & Scholarly Publication 100 40
TRIMESTER 3
1 Project 600

Job Opportunities :
• Data Scientist
• Business Analyst Consultant
• Business Analyst Industry Expert
• Business Analyst Project Manager
• Data Analyst
• Data Analyst SAS Programmer
• Big Data Analyst
• Data Warehousing Expert
• Business Intelligence Expert
• Data Warehousing and BA Architecture
• Data Mining Expert
• Cloud Computing Consultants
• Accelerated Promotions in existing jobs

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