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Insoft Services er en av få opplæringsleverandører i EMEAR som tilbyr hele spekteret av Cisco-sertifisering og spesialisert teknologiopplæring.

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Cisco Sertifisering

Opplev en blandet læringstilnærming som kombinerer det beste av instruktørledet opplæring og e-læring i eget tempo for å hjelpe deg med å forberede deg til sertifiseringseksamen.

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Cisco Learning Credits

Cisco Learning Credits (CLC) er forhåndsbetalte opplæringskuponger innløst direkte med Cisco som gjør planleggingen for suksessen din enklere når du kjøper Cisco-produkter og -tjenester.

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Etterutdanning

Cisco Continuing Education Program tilbyr alle aktive sertifiseringsinnehavere fleksible alternativer for å resertifisere ved å fullføre en rekke kvalifiserte opplæringselementer.

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Cisco Digital Learning

Sertifiserte ansatte er verdsatte eiendeler. Utforsk Ciscos offisielle digitale læringsbibliotek for å utdanne deg gjennom innspilte økter.

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Cisco Business Enablement

Cisco Business Enablement Partner Program fokuserer på å skjerpe forretningsferdighetene til Cisco Channel Partners og kunder.

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Fortinet Sertifisering

Fortinet Network Security Expert (NSE)-programmet er et opplærings- og sertifiseringsprogram på åtte nivåer for å lære ingeniører om nettverkssikkerheten for Fortinet FW-ferdigheter og -erfaring.

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Fortinet-opplæring

Insoft er anerkjent som Fortinet Autorisert Opplæringssenter på utvalgte steder i EMEA.

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Fortinet opplæringskatalog

Utforsk et bredt utvalg av Fortinet Schedule på tvers av forskjellige land så vel som online kurs.

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ATC-status

Sjekk atc-statusen vår på tvers av utvalgte land i Europa.

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Pakker for Fortinet-tjenester

Insoft Services har utviklet en spesifikk løsning for å effektivisere og forenkle prosessen med å installere eller migrere til Fortinet-produkter.

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Microsoft-opplæring

Insoft Services gir Microsoft opplæring i EMEAR. Vi tilbyr Microsofts tekniske opplærings- og sertifiseringskurs som ledes av instruktører i verdensklasse.

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Extreme-opplæring

Lær eksepsjonell kunnskap og ferdigheter i ekstreme nettverk.

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Teknisk sertifisering

Vi tilbyr omfattende læreplan over tekniske kompetanseferdigheter om sertifiseringsprestasjonen.

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Extreme opplæringskatalog

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ATP-akkreditering

Som autorisert opplæringspartner (ATP) sørger Insoft Services for at du får de høyeste utdanningsstandardene som er tilgjengelige.

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Løsninger og tjenester

Vi tilbyr innovativ og avansert støtte for design, implementering og optimalisering av IT-løsninger. Vår kundebase inkluderer noen av de største Telcos globalt.

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Globalt anerkjent team av sertifiserte eksperter hjelper deg med å gjøre en jevnere overgang med våre forhåndsdefinerte konsulent-, installasjons- og migrasjonspakker for et bredt spekter av Fortinet-produkter.

Om oss

Insoft Tilbyr autoriserte opplærings- og konsulenttjenester for utvalgte IP-leverandører. Finn ut hvordan vi revolusjonerer bransjen.

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    • Big Data Processing with Apache Spark

    Enroll Now
    Duration
    2 Dager
    Delivery
    (Online Og På stedet)
    Price
    Pris på forespørsel
    Processing big data in real-time is challenging due to scalability, information consistency, and fault tolerance. This Big Data Processing with Apache Spark course shows you how you can use Spark to make your overall analysis workflow faster and more efficient. You'll learn all about the core concepts and tools within the Spark ecosystem, like Spark Streaming, the Spark Streaming API, machine learning extension, and structured streaming. You'll begin by learning data processing fundamentals using Resilient Distributed Datasets (RDDs), SQL, Datasets, and Dataframes APIs. After grasping these fundamentals, you'll move on to using Spark Streaming APIs to consume data in real-time from TCP sockets, and integrate Amazon Web Services (AWS) for stream consumption. By the end of this course, you will not only have understood how to use machine learning extensions and structured streams but you will also be able to apply Spark in your own upcoming big data projects.  

    After completing this course, you will be able to:

    • Write your own Python programs that can interact with Spark
    • Implement data stream consumption using Apache Spark
    • Recognize common operations in Spark to process known data streams
    • Integrate Spark streaming with Amazon Web Services
    • Create a collaborative filtering model with Python and the movielens dataset
    • Apply processed data streams to Spark machine learning APIs

    Lesson 1: Introduction to Spark Distributed Processing

    • Introduction to Spark and Resilient Distributed Datasets
    • Operations Supported by the RDD API
    • Self-Contained Python Spark Programs
    • Introduction to SQL, Datasets, and DataFrames

    Lesson 2: Introduction to Spark Streaming

    • Streaming Architectures
    • Introduction to Discretized Streams
    • Windowing Operations
    • Introduction to Structured Streaming

    Lesson 3: Spark Streaming Integration with AWS

    • Spark Integration with AWS Services
    • Integrating AWS Kinesis and Python
    • AWS S3 Basic Functionality

    Lesson 4: Spark Streaming, ML, and Windowing Operations

    • Spark Integration with Machine Learning

    Big Data Processing with Apache Spark is for you if you are a software engineer, architect, or IT professional who wants to explore distributed systems and big data analytics. Although you don't need any knowledge of Spark, prior experience of working with Python is recommended.

    Hardware:

    For an optimal experience with the hands-on labs and other practical activities, we recommend the following hardware configuration:

    • Processor: Intel Core i5 or equivalent
    • Memory: 4GB RAM
    • Storage: 35 GB available space

     

    Software:

    • OS: Windows 7 SP1 64-bit, Windows 8.1 64-bit or Windows 10 64-bit
    • PostgreSQL 9.0 or above
    • Python 3.0 or above
    • Spark 2.3.0
    • Amazon Web Services (AWS) account
    Overview
    Processing big data in real-time is challenging due to scalability, information consistency, and fault tolerance. This Big Data Processing with Apache Spark course shows you how you can use Spark to make your overall analysis workflow faster and more efficient. You'll learn all about the core concepts and tools within the Spark ecosystem, like Spark Streaming, the Spark Streaming API, machine learning extension, and structured streaming. You'll begin by learning data processing fundamentals using Resilient Distributed Datasets (RDDs), SQL, Datasets, and Dataframes APIs. After grasping these fundamentals, you'll move on to using Spark Streaming APIs to consume data in real-time from TCP sockets, and integrate Amazon Web Services (AWS) for stream consumption. By the end of this course, you will not only have understood how to use machine learning extensions and structured streams but you will also be able to apply Spark in your own upcoming big data projects.  

    After completing this course, you will be able to:

    • Write your own Python programs that can interact with Spark
    • Implement data stream consumption using Apache Spark
    • Recognize common operations in Spark to process known data streams
    • Integrate Spark streaming with Amazon Web Services
    • Create a collaborative filtering model with Python and the movielens dataset
    • Apply processed data streams to Spark machine learning APIs

    Lesson 1: Introduction to Spark Distributed Processing

    • Introduction to Spark and Resilient Distributed Datasets
    • Operations Supported by the RDD API
    • Self-Contained Python Spark Programs
    • Introduction to SQL, Datasets, and DataFrames

    Lesson 2: Introduction to Spark Streaming

    • Streaming Architectures
    • Introduction to Discretized Streams
    • Windowing Operations
    • Introduction to Structured Streaming

    Lesson 3: Spark Streaming Integration with AWS

    • Spark Integration with AWS Services
    • Integrating AWS Kinesis and Python
    • AWS S3 Basic Functionality

    Lesson 4: Spark Streaming, ML, and Windowing Operations

    • Spark Integration with Machine Learning

    Big Data Processing with Apache Spark is for you if you are a software engineer, architect, or IT professional who wants to explore distributed systems and big data analytics. Although you don't need any knowledge of Spark, prior experience of working with Python is recommended.

    Hardware:

    For an optimal experience with the hands-on labs and other practical activities, we recommend the following hardware configuration:

    • Processor: Intel Core i5 or equivalent
    • Memory: 4GB RAM
    • Storage: 35 GB available space

     

    Software:

    • OS: Windows 7 SP1 64-bit, Windows 8.1 64-bit or Windows 10 64-bit
    • PostgreSQL 9.0 or above
    • Python 3.0 or above
    • Spark 2.3.0
    • Amazon Web Services (AWS) account
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