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Sperimenta un approccio di apprendimento misto che combina il meglio della formazione con istruttore e dell'e-learning autogestito per aiutarti a prepararti per l'esame di certificazione.

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Cisco Learning Credits

I Cisco Learning Credits (CLC) sono voucher di formazione prepagati riscattati direttamente con Cisco che semplificano la pianificazione del successo durante l'acquisto di prodotti e servizi Cisco.

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Formazione Continua

The Cisco Continuing Education Program offers all active certification holders flexible options to recertify by completing a variety of eligible training items.

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Cisco Digital Learning

Certified employees are VALUED assets. Explore Cisco official Digital Learning Library to educate yourself through recorded sessions.

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Cisco Business Enablement

The Cisco Business Enablement Partner Program focuses on sharpening the business skills of Cisco Channel Partners and customers.

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Catalogo Cisco

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Certificazioni Fortinet

Il programma Fortinet Network Security Expert (NSE) è un programma di formazione e certificazione di otto livelli per insegnare agli ingegneri la sicurezza della loro rete per le competenze e l'esperienza di Fortinet FW.

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Corsi di formazione tecnica

Insoft è riconosciuto come Fortinet Authorized Training Center in sedi selezionate in tutta l'EMEA.

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Catalogo Fortinet

Esplora un'ampia varietà di programmi Fortinet in diversi paesi e corsi online.

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Stato ATC

Controlla il nostro stato ATC in tutti i paesi selezionati in Europa.

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Fortinet Servizi Professionale

Il team riconosciuto a livello globale di esperti certificati ti aiuta a fare una transizione più fluida con i nostri pacchetti di consulenza, installazione e migrazione predefiniti per una vasta gamma di prodotti Fortinet.

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Catalogo Microsoft

Insoft Services fornisce formazione Microsoft in EMEAR. Offriamo corsi di formazione tecnica e certificazione Microsoft guidati da istruttori di livello mondiale.

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Corsi di formazione

Impara conoscenze e abilità eccezionali di Extreme Networks.Find all the Extreme Networks online and instructor led class room based calendar here.

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Certificazioni Extreme

Forniamo un curriculum completo di competenze tecniche sul conseguimento della certificazione.

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Catalogo Extreme

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Accreditamento ATP

In qualità di partner di formazione autorizzato (ATP), Insoft Services garantisce che tu riceva i più alti standard di istruzione disponibili.

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Pacchetti di consulenza

Forniamo un supporto innovativo e avanzato per la progettazione, l'implementazione e l'ottimizzazione delle soluzioni IT.La nostra base di clienti comprende alcune delle più grandi telco a livello globale.

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Il team riconosciuto a livello globale di esperti certificati ti aiuta a fare una transizione più fluida con i nostri pacchetti di consulenza, installazione e migrazione predefiniti per una vasta gamma di prodotti Fortinet.

Chi siamo

Insoft fornisce servizi di formazione e consulenza autorizzati per fornitori IP selezionati.Scopri come stiamo rivoluzionando il settore.

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  • +39 02 8704 5199
  • Prenota ora

    • Big Data Processing with Apache Spark

    Enroll Now
    Duration
    2 Giorni
    Delivery
    (Online e in loco)
    Price
    Prezzo su richiesta
    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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      Data su richiesta

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