Lokale, instructerende live Apache Spark-trainingscursussen demonstreren door handson te oefenen hoe Spark past in het Big Data-ecosysteem en hoe Spark voor data-analyse te gebruiken Apache Spark-training is beschikbaar als 'live training op locatie' of 'live training op afstand' Onsite live training kan lokaal worden uitgevoerd op het terrein van de klant in Nederland of in NobleProg bedrijfsopleidingscentra in Nederland Live-training op afstand wordt uitgevoerd via een interactieve, externe desktop NobleProg Uw lokale trainingsaanbieder.
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Getuigenissen
Richard is erg kalm en methodisch, met een analytisch inzicht - precies de kwaliteiten die nodig zijn om dit soort cursus te presenteren.
Kieran Mac Kenna
Cursus: Spark for Developers
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deel conceptdiagram en ook monster voor handen vuil
Mark Yang - FMR
Cursus: Spark for Developers
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Toepasselijke scenario's en cases
zhaopeng liu - Fmr
Cursus: Spark for Developers
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Case analyse
国栋 张
Cursus: Spark for Developers
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alle delen van deze sessie
Eric Han - Fmr
Cursus: Spark for Developers
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We weten veel meer over de hele omgeving.
John Kidd
Cursus: Spark for Developers
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De trainer heeft de klas interessant en onderhoudend gemaakt en dat helpt een hele dag met training.
Ryan Speelman
Cursus: Spark for Developers
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Ik denk dat de trainer een uitstekende manier had om humor en verhalen uit het echte leven te combineren om de onderwerpen die voor de hand liggen zeer toegankelijk te maken. Ik zou deze professor in de toekomst zeer aanbevelen.
Cursus: Spark for Developers
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Ernesto heeft uitstekend werk verricht door de concepten op hoog niveau van het gebruik van Spark en de verschillende modules ervan uit te leggen.
Michael Nemerouf
Cursus: Spark for Developers
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Dit is een van de beste praktische oefeningencursussen die ik ooit heb gevolgd.
Laura Kahn
Cursus: Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP
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Dit is een van de beste online training die ik ooit heb gevolgd in mijn 13-jarige carrière. Ga zo door!.
Cursus: Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP
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Richard was heel bereid om af te wijzen wanneer we semi-gerelateerde vragen wilden stellen over dingen die niet in de syllabus staan. Verklaringen waren duidelijk en hij was vooraan over waarschuwingen in elk advies dat hij ons gaf.
ARM Limited
Cursus: Spark for Developers
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De VM ik vond heel veel De leraar was zeer goed geïnformeerd over het onderwerp en andere onderwerpen, hij was erg mooi en vriendelijk Ik vond de faciliteit in Dubai.
Safar Alqahtani - Elm Information Security
Cursus: Big Data Analytics in Health
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Oefen taken
Pawel Kozikowski - GE Medical Systems Polska Sp. Zoo
Cursus: Python and Spark for Big Data (PySpark)
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Ajay was erg vriendelijk, behulpzaam en ook goed geïnformeerd over het onderwerp dat hij besprak.
Biniam Guulay - ICE International Copyright Enterprise Germany GmbH
Cursus: Spark for Developers
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De labo-oefeningen. Toepassing van de theorie vanaf de eerste dag in de daaropvolgende dagen.
Dell
Cursus: A Practical Introduction to Stream Processing
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De leraar heeft het trainingsprogramma aangepast aan onze huidige behoeften.
EduBroker Sp. z o.o.
Cursus: Python and Spark for Big Data (PySpark)
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Door soortgelijke oefeningen op verschillende manieren te doen, begrijp je echt wat elk onderdeel ( Hadoop / Spark, standalone / cluster) alleen en samen kan doen. Het gaf me ideeën over hoe ik mijn applicatie op mijn lokale machine zou moeten testen wanneer ik ontwikkel versus wanneer deze op een cluster wordt ingezet.
Thomas Carcaud - IT Frankfurt GmbH
Cursus: Spark for Developers
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individuele aandacht.
ARCHANA ANILKUMAR - PPL
Cursus: Python and Spark for Big Data (PySpark)
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Ga naar Spark Streaming, Databricks en AWS Redshift
Lim Meng Tee - Jobstreet.com Shared Services Sdn. Bhd.
Cursus: Apache Spark in the Cloud
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De inhoud en de kennis.
Jobstreet.com Shared Services Sdn. Bhd.
Cursus: Apache Spark in the Cloud
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Het was heel informatief. Ik heb al heel weinig ervaring met Spark en tot nu toe heeft deze cursus een zeer goede inleiding voor het onderwerp gegeven.
Intelligent Medical Objects
Cursus: Apache Spark in the Cloud
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Het was geweldig om een goed begrip van wat er gaande is onder de motorkap van Spark. Weten wat er gaande is onder de motorkap helpt om beter te begrijpen waarom uw code wel of niet doet wat je verwacht dat het doet. Veel van de opleiding was hands on die altijd geweldig is en de sectie over optimalisaties was uitzonderlijk relevant voor mijn huidige werk dat was leuk.
Intelligent Medical Objects
Cursus: Apache Spark in the Cloud
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Dit is een geweldige klas! Ik waardeer het dat Andras er heel duidelijk uitlegt wat vonk over alles is, waar het vandaan kwam en welke problemen het kan oplossen. Veel beter dan andere introducties die ik heb gezien, duik gewoon om te gebruiken hoe het moet worden gebruikt. Andras heeft een diepe kennis van het onderwerp en legt het heel goed uit.
Intelligent Medical Objects
Cursus: Apache Spark in the Cloud
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De live-voorbeelden die werden gegeven en de basisaspecten van vonk hebben getoond.
Intelligent Medical Objects
Cursus: Apache Spark in the Cloud
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1 . Juiste balans tussen concepten met hoge niveau en technische details. 2. Andras is zeer goed geïnformeerd over zijn les. 3. Oefening
Steven Wu - Intelligent Medical Objects
Cursus: Apache Spark in the Cloud
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Handen hebben op sessie / opdrachten
Poornima Chenthamarakshan - Intelligent Medical Objects
Cursus: Apache Spark in the Cloud
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Trainer aangepast de training licht op het publieksaanvraag, dus gooi wat licht op enkele diff-onderwerpen die we hebben gevraagd
Intelligent Medical Objects
Cursus: Apache Spark in the Cloud
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Zijn tempo was geweldig. Ik hield van het feit dat hij ook in theorie ging, zodat ik begrijp waarom ik de dingen zou doen die hij vraagt.
Intelligent Medical Objects
Cursus: Apache Spark in the Cloud
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Ik denk dat de trainer een uitstekende manier had om humor en verhalen uit het echte leven te combineren om de onderwerpen die voor de hand liggen zeer toegankelijk te maken. Ik zou deze professor in de toekomst zeer aanbevelen.
Cursus: Spark for Developers
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Dit is een van de beste online training die ik ooit heb gevolgd in mijn 13-jarige carrière. Ga zo door!.
Cursus: Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP
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Spark subcategorieën
Apache Spark Cursusoverzicht
Course Name
Duration
Overview
Course Name
Duration
Overview
21 hours
Overview
OBJECTIVE:
This course will introduce Apache Spark. The students will learn how Spark fits into the Big Data ecosystem, and how to use Spark for data analysis. The course covers Spark shell for interactive data analysis, Spark internals, Spark APIs, Spark SQL, Spark streaming, and machine learning and graphX.
AUDIENCE :
Developers / Data Analysts
This course will introduce Apache Spark. The students will learn how Spark fits into the Big Data ecosystem, and how to use Spark for data analysis. The course covers Spark shell for interactive data analysis, Spark internals, Spark APIs, Spark SQL, Spark streaming, and machine learning and graphX.
AUDIENCE :
Developers / Data Analysts
21 hours
Overview
This instructor-led, live training in (online or onsite) introduces Hortonworks Data Platform (HDP) and walks participants through the deployment of Spark + Hadoop solution.
By the end of this training, participants will be able to:
- Use Hortonworks to reliably run Hadoop at a large scale.
- Unify Hadoop's security, governance, and operations capabilities with Spark's agile analytic workflows.
- Use Hortonworks to investigate, validate, certify and support each of the components in a Spark project.
- Process different types of data, including structured, unstructured, in-motion, and at-rest.
By the end of this training, participants will be able to:
- Use Hortonworks to reliably run Hadoop at a large scale.
- Unify Hadoop's security, governance, and operations capabilities with Spark's agile analytic workflows.
- Use Hortonworks to investigate, validate, certify and support each of the components in a Spark project.
- Process different types of data, including structured, unstructured, in-motion, and at-rest.
14 hours
Overview
Magellan is an open-source distributed execution engine for geospatial analytics on big data. Implemented on top of Apache Spark, it extends Spark SQL and provides a relational abstraction for geospatial analytics.
This instructor-led, live training introduces the concepts and approaches for implementing geospacial analytics and walks participants through the creation of a predictive analysis application using Magellan on Spark.
By the end of this training, participants will be able to:
- Efficiently query, parse and join geospatial datasets at scale
- Implement geospatial data in business intelligence and predictive analytics applications
- Use spatial context to extend the capabilities of mobile devices, sensors, logs, and wearables
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
This instructor-led, live training introduces the concepts and approaches for implementing geospacial analytics and walks participants through the creation of a predictive analysis application using Magellan on Spark.
By the end of this training, participants will be able to:
- Efficiently query, parse and join geospatial datasets at scale
- Implement geospatial data in business intelligence and predictive analytics applications
- Use spatial context to extend the capabilities of mobile devices, sensors, logs, and wearables
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
7 hours
Overview
Alluxio is an open-source virtual distributed storage system that unifies disparate storage systems and enables applications to interact with data at memory speed. It is used by companies such as Intel, Baidu and Alibaba.
In this instructor-led, live training, participants will learn how to use Alluxio to bridge different computation frameworks with storage systems and efficiently manage multi-petabyte scale data as they step through the creation of an application with Alluxio.
By the end of this training, participants will be able to:
- Develop an application with Alluxio
- Connect big data systems and applications while preserving one namespace
- Efficiently extract value from big data in any storage format
- Improve workload performance
- Deploy and manage Alluxio standalone or clustered
Audience
- Data scientist
- Developer
- System administrator
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
In this instructor-led, live training, participants will learn how to use Alluxio to bridge different computation frameworks with storage systems and efficiently manage multi-petabyte scale data as they step through the creation of an application with Alluxio.
By the end of this training, participants will be able to:
- Develop an application with Alluxio
- Connect big data systems and applications while preserving one namespace
- Efficiently extract value from big data in any storage format
- Improve workload performance
- Deploy and manage Alluxio standalone or clustered
Audience
- Data scientist
- Developer
- System administrator
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
7 hours
Overview
Spark SQL is Apache Spark's module for working with structured and unstructured data. Spark SQL provides information about the structure of the data as well as the computation being performed. This information can be used to perform optimizations. Two common uses for Spark SQL are:
- to execute SQL queries.
- to read data from an existing Hive installation.
In this instructor-led, live training (onsite or remote), participants will learn how to analyze various types of data sets using Spark SQL.
By the end of this training, participants will be able to:
- Install and configure Spark SQL.
- Perform data analysis using Spark SQL.
- Query data sets in different formats.
- Visualize data and query results.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
- to execute SQL queries.
- to read data from an existing Hive installation.
In this instructor-led, live training (onsite or remote), participants will learn how to analyze various types of data sets using Spark SQL.
By the end of this training, participants will be able to:
- Install and configure Spark SQL.
- Perform data analysis using Spark SQL.
- Query data sets in different formats.
- Visualize data and query results.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
21 hours
Overview
In this instructor-led, live training in Nederland (onsite or remote), participants will learn how to set up and integrate different Stream Processing frameworks with existing big data storage systems and related software applications and microservices.
By the end of this training, participants will be able to:
- Install and configure different Stream Processing frameworks, such as Spark Streaming and Kafka Streaming.
- Understand and select the most appropriate framework for the job.
- Process of data continuously, concurrently, and in a record-by-record fashion.
- Integrate Stream Processing solutions with existing databases, data warehouses, data lakes, etc.
- Integrate the most appropriate stream processing library with enterprise applications and microservices.
By the end of this training, participants will be able to:
- Install and configure different Stream Processing frameworks, such as Spark Streaming and Kafka Streaming.
- Understand and select the most appropriate framework for the job.
- Process of data continuously, concurrently, and in a record-by-record fashion.
- Integrate Stream Processing solutions with existing databases, data warehouses, data lakes, etc.
- Integrate the most appropriate stream processing library with enterprise applications and microservices.
21 hours
Overview
Big data analytics involves the process of examining large amounts of varied data sets in order to uncover correlations, hidden patterns, and other useful insights.
The health industry has massive amounts of complex heterogeneous medical and clinical data. Applying big data analytics on health data presents huge potential in deriving insights for improving delivery of healthcare. However, the enormity of these datasets poses great challenges in analyses and practical applications to a clinical environment.
In this instructor-led, live training (remote), participants will learn how to perform big data analytics in health as they step through a series of hands-on live-lab exercises.
By the end of this training, participants will be able to:
- Install and configure big data analytics tools such as Hadoop MapReduce and Spark
- Understand the characteristics of medical data
- Apply big data techniques to deal with medical data
- Study big data systems and algorithms in the context of health applications
Audience
- Developers
- Data Scientists
Format of the Course
- Part lecture, part discussion, exercises and heavy hands-on practice.
Note
- To request a customized training for this course, please contact us to arrange.
The health industry has massive amounts of complex heterogeneous medical and clinical data. Applying big data analytics on health data presents huge potential in deriving insights for improving delivery of healthcare. However, the enormity of these datasets poses great challenges in analyses and practical applications to a clinical environment.
In this instructor-led, live training (remote), participants will learn how to perform big data analytics in health as they step through a series of hands-on live-lab exercises.
By the end of this training, participants will be able to:
- Install and configure big data analytics tools such as Hadoop MapReduce and Spark
- Understand the characteristics of medical data
- Apply big data techniques to deal with medical data
- Study big data systems and algorithms in the context of health applications
Audience
- Developers
- Data Scientists
Format of the Course
- Part lecture, part discussion, exercises and heavy hands-on practice.
Note
- To request a customized training for this course, please contact us to arrange.
21 hours
Overview
Apache Spark's learning curve is slowly increasing at the begining, it needs a lot of effort to get the first return. This course aims to jump through the first tough part. After taking this course the participants will understand the basics of Apache Spark , they will clearly differentiate RDD from DataFrame, they will learn Python and Scala API, they will understand executors and tasks, etc. Also following the best practices, this course strongly focuses on cloud deployment, Databricks and AWS. The students will also understand the differences between AWS EMR and AWS Glue, one of the lastest Spark service of AWS.
AUDIENCE:
Data Engineer, DevOps, Data Scientist
AUDIENCE:
Data Engineer, DevOps, Data Scientist
21 hours
Overview
This instructor-led, live training in Nederland (online or onsite) is aimed at software engineers who wish to stream big data with Spark Streaming and Scala.
By the end of this training, participants will be able to:
- Create Spark applications with the Scala programming language.
- Use Spark Streaming to process continuous streams of data.
- Process streams of real-time data with Spark Streaming.
By the end of this training, participants will be able to:
- Create Spark applications with the Scala programming language.
- Use Spark Streaming to process continuous streams of data.
- Process streams of real-time data with Spark Streaming.
14 hours
Overview
This instructor-led, live training in Nederland (online or onsite) is aimed at data scientists who wish to use the SMACK stack to build data processing platforms for big data solutions.
By the end of this training, participants will be able to:
- Implement a data pipeline architecture for processing big data.
- Develop a cluster infrastructure with Apache Mesos and Docker.
- Analyze data with Spark and Scala.
- Manage unstructured data with Apache Cassandra.
By the end of this training, participants will be able to:
- Implement a data pipeline architecture for processing big data.
- Develop a cluster infrastructure with Apache Mesos and Docker.
- Analyze data with Spark and Scala.
- Manage unstructured data with Apache Cassandra.
21 hours
Overview
This instructor-led, live training in Nederland (online or onsite) is aimed at engineers who wish to set up and deploy Apache Spark system for processing very large amounts of data.
By the end of this training, participants will be able to:
- Install and configure Apache Spark.
- Quickly process and analyze very large data sets.
- Understand the difference between Apache Spark and Hadoop MapReduce and when to use which.
- Integrate Apache Spark with other machine learning tools.
By the end of this training, participants will be able to:
- Install and configure Apache Spark.
- Quickly process and analyze very large data sets.
- Understand the difference between Apache Spark and Hadoop MapReduce and when to use which.
- Integrate Apache Spark with other machine learning tools.
21 hours
Overview
This instructor-led, live training in Nederland (online or onsite) is aimed at developers who wish to carry out big data analysis using Apache Spark in their .NET applications.
By the end of this training, participants will be able to:
- Install and configure Apache Spark.
- Understand how .NET implements Spark APIs so that they can be accessed from a .NET application.
- Develop data processing applications using C# or F#, capable of handling data sets whose size is measured in terabytes and pedabytes.
- Develop machine learning features for a .NET application using Apache Spark capabilities.
- Carry out exploratory analysis using SQL queries on big data sets.
By the end of this training, participants will be able to:
- Install and configure Apache Spark.
- Understand how .NET implements Spark APIs so that they can be accessed from a .NET application.
- Develop data processing applications using C# or F#, capable of handling data sets whose size is measured in terabytes and pedabytes.
- Develop machine learning features for a .NET application using Apache Spark capabilities.
- Carry out exploratory analysis using SQL queries on big data sets.
35 hours
Overview
This instructor-led, live training in Nederland (online or onsite) is aimed at system administrators who wish to learn how to set up, deploy and manage Hadoop clusters within their organization.
By the end of this training, participants will be able to:
- Install and configure Apache Hadoop.
- Understand the four major components in the Hadoop ecoystem: HDFS, MapReduce, YARN, and Hadoop Common.
- Use Hadoop Distributed File System (HDFS) to scale a cluster to hundreds or thousands of nodes.
- Set up HDFS to operate as storage engine for on-premise Spark deployments.
- Set up Spark to access alternative storage solutions such as Amazon S3 and NoSQL database systems such as Redis, Elasticsearch, Couchbase, Aerospike, etc.
- Carry out administrative tasks such as provisioning, management, monitoring and securing an Apache Hadoop cluster.
By the end of this training, participants will be able to:
- Install and configure Apache Hadoop.
- Understand the four major components in the Hadoop ecoystem: HDFS, MapReduce, YARN, and Hadoop Common.
- Use Hadoop Distributed File System (HDFS) to scale a cluster to hundreds or thousands of nodes.
- Set up HDFS to operate as storage engine for on-premise Spark deployments.
- Set up Spark to access alternative storage solutions such as Amazon S3 and NoSQL database systems such as Redis, Elasticsearch, Couchbase, Aerospike, etc.
- Carry out administrative tasks such as provisioning, management, monitoring and securing an Apache Hadoop cluster.
35 hours
Overview
MLlib is Spark’s machine learning (ML) library. Its goal is to make practical machine learning scalable and easy. It consists of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, as well as lower-level optimization primitives and higher-level pipeline APIs.
It divides into two packages:
-
spark.mllib contains the original API built on top of RDDs.
-
spark.ml provides higher-level API built on top of DataFrames for constructing ML pipelines.
Audience
This course is directed at engineers and developers seeking to utilize a built in Machine Library for Apache Spark
It divides into two packages:
-
spark.mllib contains the original API built on top of RDDs.
-
spark.ml provides higher-level API built on top of DataFrames for constructing ML pipelines.
Audience
This course is directed at engineers and developers seeking to utilize a built in Machine Library for Apache Spark
21 hours
Overview
This course is aimed at developers and data scientists who wish to understand and implement AI within their applications. Special focus is given to Data Analysis, Distributed AI and NLP.
28 hours
Overview
In this instructor-led, live training in Nederland, participants will learn about the technology offerings and implementation approaches for processing graph data. The aim is to identify real-world objects, their characteristics and relationships, then model these relationships and process them as data using a Graph Computing (also known as Graph Analytics) approach. We start with a broad overview and narrow in on specific tools as we step through a series of case studies, hands-on exercises and live deployments.
By the end of this training, participants will be able to:
- Understand how graph data is persisted and traversed.
- Select the best framework for a given task (from graph databases to batch processing frameworks.)
- Implement Hadoop, Spark, GraphX and Pregel to carry out graph computing across many machines in parallel.
- View real-world big data problems in terms of graphs, processes and traversals.
By the end of this training, participants will be able to:
- Understand how graph data is persisted and traversed.
- Select the best framework for a given task (from graph databases to batch processing frameworks.)
- Implement Hadoop, Spark, GraphX and Pregel to carry out graph computing across many machines in parallel.
- View real-world big data problems in terms of graphs, processes and traversals.
21 hours
Overview
In this instructor-led, live training in Nederland, participants will learn how to use Python and Spark together to analyze big data as they work on hands-on exercises.
By the end of this training, participants will be able to:
- Learn how to use Spark with Python to analyze Big Data.
- Work on exercises that mimic real world cases.
- Use different tools and techniques for big data analysis using PySpark.
By the end of this training, participants will be able to:
- Learn how to use Spark with Python to analyze Big Data.
- Work on exercises that mimic real world cases.
- Use different tools and techniques for big data analysis using PySpark.
Aankomende Spark cursussen
17-11-2021 09:30
Amsterdam
21 hours
15-12-2021 09:30
Amsterdam
21 hours
20-12-2021 09:30
Amsterdam
28 hours
22-12-2021 09:30
Amsterdam
14 hours
23-12-2021 09:30
Amsterdam
7 hours
Weekend Spark cursus, Avond Spark training, Avond Spark opleiding Apache Spark boot camp, Spark instructeur geleid, Weekend Apache Spark training, Avond Spark cursus, Apache Spark coaching, Spark instructeur, Apache Spark trainer, Apache Spark training cursus, Apache Spark lessen, Apache Spark on-site, Apache Spark privé cursus, Apache Spark een op een training, Spark op locatie, Weekend Apache Spark opleiding
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