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File: Itdb405 Big Data Analytics
course name big data analytics course code itdb405 pre requisite itdb303 fundamentals of big data credit hours 3 passing grade c level b tech no of theory hrs 1 no ...

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                     Course Name :  Big Data Analytics                                                Course Code  : ITDB405 
                     Pre Requisite  : ITDB303-Fundamentals of Big Data                                Credit Hours  :  3 
                     Passing Grade : C                                                                Level: B.Tech 
                     No. of Theory Hrs: 1                                                             No. of Practical Hrs : 4 
                     Goal: To adequately prepare the students to offer the best practices in big data analytics and to provide 
                     them with the tools, techniques and industry accepted methodologies for data analytics. 
                     Objectives:   
                     Upon completion of this course, the students should be able to:  
                           1.  Investigate the big data analytic techniques for useful business applications. 
                      
                           2.  Explore an open source software to perform exploratory Data Analytics 
                                 
                           3.  Work with a NoSQL document database model 
                                                                       Outcomes                                                         Methodologies 
                     Upon completion of this course, the students should be able to: 
                           1.  Explore the fundamental concepts of big data analytics                                                        Theory 
                           2.   Devise the statistical concepts such as descriptive statistics, probability theory, test                    Practical 
                                of significance etc and their application in business 
                           3.  Perform  basic  analytical  techniques  such  as  data  exploration,  data                                   Practical 
                                preparation and data visualization using R 
                           4.  Use visualization techniques in R                                                                                   
                           5.  Perform sentiment analysis using R                                                                           Practical 
                           6.  Illustrate  the  basic  concepts  of  MongoDB  such  as  schema  design,  data                               Practical 
                                querying, insertion, updating, deletion, etc 
                           7.  Use R to analyze a MongoDB database                                                                          Practical 
                     Software & Hardware Tools: RStudio, MongoDB 
                     Text Book: 
                           1)  Vignesh Prajapati, “Big Data Analytics with R and Hadoop”, Packt Publishing Ltd, 2013 
                     Reference Book:  
                           1)  M.Michael, M. Chambers, Ambiga Dhirai, “Big Data, Big Analytics: Emerging Business 
                                Intelligence and Analytic Trends for Today's Businesses”,Wiley,2013,ISBN-13: 978-
                                1118147603 
                           2)  Norman Matloff,” The Art of R Programming: A Tour of Statistical Software Design”,No Starch 
                                Press,2011,ISBN-13:978-1593273842 
                           3)  Rick Copeland,  “MongoDB Applied Design Patterns” , O'Reilly Media,2013, Ebook ISBN: 978-
                                1-4493-4003-2 (Safari online book) 
                      
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...Course name big data analytics code itdb pre requisite fundamentals of credit hours passing grade c level b tech no theory hrs practical goal to adequately prepare the students offer best practices in and provide them with tools techniques industry accepted methodologies for objectives upon completion this should be able investigate analytic useful business applications explore an open source software perform exploratory work a nosql document database model outcomes fundamental concepts devise statistical such as descriptive statistics probability test significance etc their application basic analytical exploration preparation visualization using r use sentiment analysis illustrate mongodb schema design querying insertion updating deletion analyze hardware rstudio text book vignesh prajapati hadoop packt publishing ltd reference m michael chambers ambiga dhirai emerging intelligence trends today s businesses wiley isbn norman matloff art programming tour starch press rick copeland appl...

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