Training ID
Duration 35 hours
Price:

 

Schedule
Coming Soon !!!

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Premises
Code.Hub Training Center
Leof. Alexandras 205, Athina 115 23
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Registration to this training implies full compliance and acceptance of the Code.Learn Terms & Conditions.

Description

Big data is an evolving term that describes any voluminous amount of structured, semi-structured, and unstructured data that has the potential to be mined for information. Today, data has become capital, and innovative solutions have emerged to analyze and obtain value from large and fastly received data.

Through this Code.Learn Big Data program, certified by Athens Tech College, a holistic approach will be followed in order to introduce, familiarize, and expose the participants to all the key concepts and applications of big data. Participants will have complete hands-on programming, implementation, and deployment experience by using most of the cutting-edge big data technologies and systems.


Key Objectives

The key learning objectives of this program can be summarized as follows:

  • Big data problem, dimensions, and application areas
  • Big data modeling, data management and systems
  • Hadoop ecosystem (HDFS, MapReduce, YARN, and Common)
  • Key components (Spark, Hive, Pig, Oozie and Sqoop and others)
  • Kafka (real-time data pipelines and streaming apps)
  • Big data Integration and processing project
  • Mining of Massive Datasets architecture

Target Audience

Higher education graduates in one of the following fields:

  • Computer Science,
  • Ιnformatics,
  • Software Engineering,
  • Web and Mobile Development,
  • Computer Engineering,
  • or any other relevant area

Prerequisite Knowledge

Some hands-on experience with relational databases and some basic knowledge of programming concepts will be beneficial.


Classroom

Sessions can be carried out:

  • Live in a physical classroom
  • Live online through video conferencing environments
  • Using a Hybrid combination of both live physical and online approaches

The teaching method will depend on the conditions at the time the training will run and on the participants’
preferences.