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      • Associate Big Data Engineer

      Associate Big Data Engineer

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      Trending
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      ₹70,566.97
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      Associate Big Data Engineer

      Course Summary:

      ITET Big Data Certification Course “Associate Big Data Engineer” is a high-end hands on training programme designed with the aim to enable Graduates and Professionals to build a sparkling career in the Big data domain.

      Prerequisite:

      • Basic knowledge of Big data ecosystem, Hadoop & Spark.
      • Basic knowledge of SQL and Python.

      About the Trainer:

      Basheer Ahamed Fazal is a hands-on technical architect with 13 years of experience in software design & development such as Web Application,Enterprise integrations, Micro services and Event driven applications.
      He actively contributes for evangelising Data Science, Predictive Analytics and Machine Learning to replace the existing expert systems. He has got ample experience in building highly available, secure, robust, concurrent and
      scalable systems. He is a specialist in Python (OOPs, Flask, Numpy, Pandas,scikit-learn), Node.js, Java, J2EE (Struts, Spring, Hibernate), JavaScript, Rubyon Rails and Ajax in Operating systems like Mac, Windows and Linux.
      Expertise in designing and developing REST based applications and Micro services by adhering to the Security standards. He also possesses expert level knowledge and experience in Design Patterns, Security Threat Modelling,
      Data modelling and Object-Oriented Design. The Frameworks and Tools that he worked on include: Flask, Django, DropWizard, Netty, Play Framwork, Java8, Spring, Spring Boot, Liquibase, Restful Web services, Hibernate,
      quartz, JUnit, TestNG, Mockito, Express.js, Hapi.js, Mocha.js, Chai.js, Magic draw, Argo Uml, Jmeter, Jprofiler, Soap UI, eclipse etc, AWS EC2, LAMDA, Cucumber, Docker, Ansible, Kafka, SQS, Google Cloud Platform (Google
      Functions, PubSub, Monitoring, Google compute Engine, Google Data Flow,Google ML).

      Topics Covered:

      Hadoop installation – Psuedo HA and non-HA, Hadoop, Spark, Hive, Flume,Kafka, Capstone Project Guidance.

      Course Duration: 28hrs

      Certifications to appear:

      • CCA175 – Spark and Hadoop Developer Certification.

       

       

      Course Features

      • Lectures 38
      • Quizzes 0
      • Duration 50 hours
      • Skill level All levels
      • Language English
      • Students 5
      • Assessments Yes
      ITET CoursesTrendingAssociate Big Data Engineer
      • Session-01 3

        • Lecture1.1
          Overview of Big data and Hadoop ecosystem 03 hour 57 min
        • Lecture1.2
          Setting up Hadoop in pseudo mode
        • Lecture1.3
          Running a map reduce job and understanding its internals 03 hour 24 min
      • Session-02 2

        • Lecture2.1
          Setting up real Hadoop clusters 03 hour 51 min
        • Lecture2.2
          Setting up configurations for HA cluster
      • Session-03 4

        • Lecture3.1
          Executing set of HDFS commands
        • Lecture3.2
          Understanding Hive architecture and usage of Hive
        • Lecture3.3
          Setting up Hive on top of Hadoop 05 hour 21 min
        • Lecture3.4
          Data models in Hive 01 hour 34 min
      • Session-04 3

        • Lecture4.1
          Continuation of Data models
        • Lecture4.2
          An example project to demonstrate end to Hive usage (pushing data and creating hive tables and running SQL queries)
        • Lecture4.3
          Summary
      • Session-05 2

        • Lecture5.1
          Understanding Data ingestion (DI)
        • Lecture5.2
          Tools and techniques for DI
      • Session-06 2

        • Lecture6.1
          Setting up Sqoop to import RDBMS data into Hadoop
        • Lecture6.2
          Setting up Flume to ingest data into HDFS
      • Session-07 2

        • Lecture7.1
          Understanding Kafka, its architecture and its ability as messaging bus
        • Lecture7.2
          Setting up Kafka and demonstrating a simple producing and consuming system
      • Session-08 4

        • Lecture8.1
          Spark and its architecture
        • Lecture8.2
          Sparks vs Hadoop
        • Lecture8.3
          Simple job submission to Spark
        • Lecture8.4
          Summary
      • Session-09 3

        • Lecture9.1
          Understandings RDDs and DAGS.
        • Lecture9.2
          Spark’s Data structures (RDDs, Dataframes & Datasets)
        • Lecture9.3
          Examples
      • Session-10 2

        • Lecture10.1
          Setting up PySpark context
        • Lecture10.2
          Batch processing using Pyspark
      • Session-11 2

        • Lecture11.1
          Stream processing using Spark Streaming (Kafka as streaming agent)
        • Lecture11.2
          Lab setup to pull data into spark and run realtime analytics
      • Session-12 4

        • Lecture12.1
          Overall summary
        • Lecture12.2
          Explanation on assignment project
        • Lecture12.3
          Q&A
        • Lecture12.4
          Career guidance and way forward
      • Add-on Session1 2

        • Lecture13.1
          Follow up on progress
        • Lecture13.2
          Resolving issues/impediments
      • Add-on Session2 3

        • Lecture14.1
          Follow up on progress
        • Lecture14.2
          Resolving issues/impediments
        • Lecture14.3
          Learning outcome

      Students List

      • Atavur
        Atavur
        Learning0%
      • Siraj
        Siraj
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      • Mumin
        Mumin
        Learning0%
      • Haleema Pk
        Haleema Pk
        Learning0%
      • Dr.Haleema
        Dr.Haleema
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      ITET Admin

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