Spark training in Bellandur Bangalore

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Bellandur, Bangalore

Course ID: 31341

Bellandur, Bangalore

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About Padmapriya Chitturi

(0) So far, trained 150+ working professionals.
(1) Author of “Spark for Data Science Cook Book” – Packet Publishers.
(2) Delivering Spark training's since 2015.
(3) Spark committer and speaker.
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About the Course

Thank you for taking time and exploring opportunity with BigDataHub. We are a group of working professionals delivering Hadoop and Spark Training's out of passion. I hope that we can help you to drift your career to BigData. Feel free to call back. Some of the highlights of the course are given below.

(1) 75 hours of training out of which 45+ hours of hands-on.
(2) Trainer have 6+ years of industry experience and 3+ years of teaching experience.
(3) 9 students/batch and 6 month assistance post completion of the course.
(4) Study material will be given along with exercises and interview questions for every module.
(5) Placement assistance will be provided based on the candidature.


 


Course Highlights


Scala | Python | Spark Core | Spark Streaming with Kafka | Spark SQL, Data frames & Data Sets | Machine Learning with Spark(MLLib) | SparkR | Spark Integrations With HDFS, HBase, Cassandra, MongoDB, Redis, Elastic Search, Flume and many others


 


Scala Basics (8 Hours)


Comparison between different Programming Paradigms | Introduction | Scala Installation, sbt, Project Creation Steps | Scala Constructs | Control Structures - if-else, loops, match clause | Functions – declaration, partial functions, anonymous functions | Lazy evaluation | Immutable Collections - Array, List, Map & Set | Mutable Collections – Array Buffer, List Buffer, Mutable Map | Classes & Objects | Singleton object / companion class | Traits | Exception Handling (try-catch, Except, Try)


 


Python Basics (4 Hours)


Python Introduction | Installation | Python Language constructs | Python Functions | Python Modules | Python Classes & Objects | Python tools pip, PyPi | Python analytical modules like SciPy, NumPy, Pandas


 


Please visit http://www.bigdatahub.org/ for more details.

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