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Engineering Big Data with R and Hadoop Ecosystem

Engineering Big Data with R and Hadoop Ecosystem

Online Instructor led Course

Platform: A-View

35,000

No Reviews Yet
2 Interested

About the Course


This course thoroughly trains candidates on the following techniques:

SQL querying (with a focus on statistical analysis)
Hadoop and Map Reduce methods of programming
Designing columnar databases

From a tools perspective, this course introduces you to Hadoop. You will learn one of the most powerful combinations of Big Data, viz., "R and Hadoop".

In addition, all the essential content required to build powerful Big Data processing applications and to acquire respected industry certifications like Cloudera's Apache Hadoop Developer certification will be covered in the course. The emphasis is not on abstract theory or on mindless coding. The emphasis is, instead, placed on learning concepts and real-world programming techniques.

Topics Covered

Introduction to Big Data & Applications
The Hadoop Eco-system
Parallel architectures and concurrent algorithms
Distributed File Systems, GFS & HDFS
HDFS (continued), CDH4 HDFS
Map Reduce
Map Reduce (continued)
Map Reduce (continued), YARN, Hadoop Streaming
Sqoop, Hive
R-Hadoop
NoSQL databases including HBase
PIG, Oozie
Machine Learning on Hadoop - Mahout
Text Search Application on Hadoop
Other ecosystem components
Text Classification, text clustering
Graph processing & Applications including SSSP
PageRank, BSP, Hama
Pregel, Giraph, Social Network Mining
Certification & Wrap up

Who should attend

Working professionals, managers and recent graduates are eligible for the program. We do not specify any academic background requirements.

Pre-requisites

Elementary programming skills.

What you need to bring

Laptop"

Key Takeaways

SQL querying (with a focus on statistical analysis)
Hadoop and Map Reduce methods of programming
Designing columnar databases
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Date and Time

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About the Trainer

Dr. Sreerama K. Murthy

Ph.D. (Computer Science) - Johns Hopkins University


18 years of work experience after Ph.D.
21 US Patent applications (8 issued), 2 Indian patent applications
Seats Left-

Students Interested 2

Course Id: 14538