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Bigdata training Dindigul TamilNadu, bigdata training institutes Dindigul TamilNadu

List of Best Bigdata training Dindigul TamilNadu, bigdata training institutes Dindigul TamilNadu with address, Phone numbers, course fee, student reviews and training course learning at Dindigul area in TamilNadu City. As of June 25, 2018, We have total of 1 Bigdata training institutes in and around also near to Dindigul in TamilNadu.

 

 

training institutes KALVI INSTITUTE Higher Education and Research
TamilNadu - Dindigul
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training institute
Address: 91 1st Floor, Sona Tower, New Agraharam, Palani Road, Dindigul. TamilNadu-624001
KALVI INSTITUTE Higher Education and Research Institute provides placement Bigdata training in Dindigul , Apache Cassandra, Puppet, Apache Spark, BigData Certification, Big Data Analytics training classes at Dindigul.
 
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Bigdata related Training courses in dindigul

 

 

 

 

 

 

 

Best Bigdata training institutes in dindigul, tamilnadu - Training Requirements

List of training requirements recieved for Best Bigdata training centers in dindigul, tamilnadu.


S.REKHA (dindigul TamilNadu on 11-Oct-2015 )
I am doing m.sc(computer science) in final year,I want confiramation certificate and project is issue any Bangalore software company,this is very important this,can u help this ur institute,if doing plz inform to me, Thanking you - bigdata training in tamilnadu (dindigul)
 


 

Bigdata course Content / syllabus at dindigul, tamilnadu.

We gathered most widely used Bigdata course content used by training institutes in dindigul,tamilnadu. The Bigdata course syllabus covers basic to advanced level and it may vary based on Bigdata training classes offered in dindigul.

 

1.Big Data Analytics introduction
1.Big Data overview
2.What is a data scientist
3.What are the roles of a data scientist
4.Big Data Analytics in industry

2.Data analytics lifecycle
1.Data Discovery
2.Data Preparation
3.Data Model Planning
4.Data Model Building
5.Data Insights

3.Data Analytic Methods Using R
1.Introduction to R
2.Analyzing and Exploring the Data
3.Model Building and Evaluation
4.Machine learning-Theory and Methods
5. Introduction to analytics for unstructured data-MapReduce and Hadoop




 

 

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