M TECH Big Data & Block Chain
Master
Online
Description
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Type
Master
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Methodology
Online
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Duration
2 Years
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Start date
Different dates available
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Online campus
Yes
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Delivery of study materials
Yes
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Support service
Yes
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Personal tutor
Yes
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Virtual classes
Yes
The demand for blockchain developers and big data analysts are highly in demand. With a curriculum designed as a blend of big data and blockchain, IIT Patna aims at nurturing future leaders with adequate skill sets to meet the need of the hour. Blockchain plays a significant role in adding an extra data layer for the big data analytics process. The Executive Masters in Blockchain and Big Data course by IIT Patna aims to offer students a comprehensive vision of the technologies of decentralization, blockchains, and big data analysis. An opportunity to become the protagonist of a revolution in the making, which demands professionals with specific training in the most sophisticated companies and organizations.
Facilities
Location
Start date
Start date
About this course
specialist
B tech it or cs
Reviews
Subjects
- Management
- M&A
- Big Data
- Blockchain
- Technology
Teachers and trainers (1)
SNEHA SHARMA
ENGINEERING JOBS
Course programme
NIT – I : Big Data Analytics:What is big data, History of Data Management; Structuring Big Data; Elements of Big Data; Big Data Analytics; distributed and Parallel Computing for Big Data; Big Data Analytics: What is Big Data Analytics, What Big Data Analytics Isn’t, Why this sudden Hype Around Big Data Analytics, Classification of Analytics, Greatest Challenges that Prevent Business from Capitalizing Big Data; Top Challenges Facing Big Data; Why Big Data Analytics Important; Data Science; Data Scientist; Terminologies used in Big Data Environments; Basically Available Soft State Eventual Consistency (BASE); Open source Analytics Tools
UNIT – II : Understanding Analytics and Big Data:Comparing Reporting and Analysis, Types of Analytics; Points to Consider during Analysis; Developing an Analytic Team; Understanding Text Analytics; Analytical Approach and Tools to Analyze Data: Analytical Approaches; History of Analytical Tools; Introducing Popular Analytical Tools; Comparing Various Analytical Tools.
UNIT – III : Understanding Map Reduce Fundamentals and HBase :The MapReduce Framework; Techniques to Optimize MapReduce Jobs; Uses of MapReduce; Role of HBase in Big Data Processing; Storing Data in Hadoop : Introduction of HDFS, Architecture, HDFC Files, File system types, commands, org.apache.hadoop.io package, HDF, HDFS High
UNIT – IV : Big Data Technology Landscape and Hadoop :NoSQL, Hadoop; RDBMS versus Hadoop; Distributed Computing Challenges; History of Hadoop; Hadoop Overview; Use Case of Hadoop; Hadoop Distributors; HDFC (Hadoop Distributed File System), HDFC Daemons, read,write, Replica Processing of Data with Hadoop; Managing Resources and Applications with Hadoop YARN.
UNIT – V : Social Media Analytics and Text Mining:Introducing Social Media; Key elements of Social Media; Text mining; Understanding Text Mining Process; Sentiment Analysis, Performing Social Media Analytics and Opinion Mining on Tweets;
Mobile Analytics: Introducing Mobile Analytics; Define Mobile Analytics; Mobile Analytics and Web Analytics; Types of Results from Mobile Analytics; Types of Applications for Mobile Analytics; Introducing Mobile Analytics Tools;Availability; Introducing HBase, Architecture, Storing Big Data with HBase , Interacting with the Hadoop Ecosystem; HBase in Operations Programming with HBase; Installation, Combining HBase and HDFS;
M TECH Big Data & Block Chain