Місцеві, інструктор під керівництвом жити Apache свічки навчальних курсів демонструють через практичний практиці, як іскри вписується в велику екосистему даних, і як використовувати іскру для аналізу даних.
Apache Spark навчання доступне як "на місці навчання" або "дистанційне навчання жити". На місці навчання в прямому ефірі може здійснюватися на місцевому рівні в україні або в Неbleprog корпоративні навчальні центри в україні. Дистанційне навчання в прямому ефірі здійснюється шляхом інтерактивного, віддаленого робочого стола.
Nobleпрога-ваш місцевий навчальний провайдер
Machine Translated
Відгуки
Річард дуже спокійний і методичний, з аналітичними проникливістю-саме ті якості, які необхідно представити такого роду звичайно.
Kieran Mac Kenna
Курси: Spark for Developers
Machine Translated
Можливі сценарії та випадки
zhaopeng liu - Fmr
Курси: Spark for Developers
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Приклад дослідження
国栋 张
Курси: Spark for Developers
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Всі частини сесії
Eric Han - Fmr
Курси: Spark for Developers
Machine Translated
Ми знаємо набагато більше про все навколишнє середовище.
John Kidd
Курси: Spark for Developers
Machine Translated
Тренер зробив клас цікавим і цікавим, який допомагає зовсім небагато з усім днем навчання.
Ryan Speelman
Курси: Spark for Developers
Machine Translated
Я думаю, що тренер був відмінним стилем поєднання гумору і реальних історій життя, щоб предмети на руку дуже доступним. Я дуже рекомендую цей професор в майбутньому.
Курси: Spark for Developers
Machine Translated
Ернесто зробив велику роботу, пояснивши високого рівня концепцій використання іскри і різних його модулів.
Michael Nemerouf
Курси: Spark for Developers
Machine Translated
Це один із найкращих практичних занять із програмування вправ, які я коли-небудь брав.
Laura Kahn
Курси: Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP
Machine Translated
Це одна з кращих якість онлайн навчання я коли-небудь прийнятих в моїй 13-річної кар'єри. Слідкуйте за велику роботу!.
Курси: Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP
Machine Translated
Річард був дуже готовий відступити, коли хотіли поставити запитання, пов'язані з напівзалежними, про речі, які не входять до навчальної програми. Пояснення були зрозумілими, і він висував попередження про застереження в будь-якій пораді, яку він дав нам.
ARM Limited
Курси: Spark for Developers
Machine Translated
VM мені дуже сподобалося Вчитель був дуже обізнаний про тему, а також інші теми, він був дуже приємний і дружній Мені сподобався об'єкт в Дубаї.
Safar Alqahtani - Elm Information Security
Курси: Big Data Analytics in Health
Machine Translated
практичні завдання
Pawel Kozikowski - GE Medical Systems Polska Sp. Zoo
Курси: Python and Spark for Big Data (PySpark)
Machine Translated
Аджай був дуже доброзичливим, корисним і також обізнаним з обговорюваною темою.
Biniam Guulay - ICE International Copyright Enterprise Germany GmbH
Курси: Spark for Developers
Machine Translated
Лабораторні вправи. Застосовує теорію з першого дня в наступні дні.
Dell
Курси: A Practical Introduction to Stream Processing
Machine Translated
Керівництво адаптувала програму підготовки до наших нинішніх потреб.
EduBroker Sp. z o.o.
Курси: Python and Spark for Big Data (PySpark)
Machine Translated
Виконання подібних вправ різними способами справді допомагає зрозуміти, що кожен компонент ( Hadoop / Spark, автономний / кластер) може робити самостійно та разом. Це дало мені уявлення про те, як я повинен перевірити свою програму на своїй локальній машині, коли я розробляю проти, коли вона розгорнута на кластері.
Thomas Carcaud - IT Frankfurt GmbH
Курси: Spark for Developers
Machine Translated
індивідуальної уваги.
ARCHANA ANILKUMAR - PPL
Курси: Python and Spark for Big Data (PySpark)
Machine Translated
Докладніше вивчити тампрук, BASTRONICKS та AWS RedShift
Lim Meng Tee - Jobstreet.com Shared Services Sdn. Bhd.
Курси: Apache Spark in the Cloud
Machine Translated
Зміст і знання.
Jobstreet.com Shared Services Sdn. Bhd.
Курси: Apache Spark in the Cloud
Machine Translated
Це було дуже інформативним. У мене був дуже мало досвіду з іскри до початку і так давно цей курс забезпечив дуже хороше введення в предмет.
Intelligent Medical Objects
Курси: Apache Spark in the Cloud
Machine Translated
Було здорово отримати розуміння того, що відбувається під капотом Іскри. Знаючи, що відбувається під капотом допомагає краще зрозуміти, чому ваш код або не робить те, що ви очікуєте, що він буде робити. Багато навчання було руки, на яких завжди більше, і розділ про оптимізацію був виключно актуальним для моєї поточної роботи, яка була хороша.
Intelligent Medical Objects
Курси: Apache Spark in the Cloud
Machine Translated
Це чудовий клас! Я найбільшу ціную, що Андри пояснюють дуже чітко, що все іскла, як з нього, і які проблеми це здатне вирішити. Набагато краще, ніж інші вступні, які я бачив, що просто занурюється в використання його. Андра має глибоке знання теми і дуже пояснює речі.
Intelligent Medical Objects
Курси: Apache Spark in the Cloud
Machine Translated
Живі приклади, які були надані і показали основні аспекти іскри.
Intelligent Medical Objects
Курси: Apache Spark in the Cloud
Machine Translated
1 . Правий баланс між концепціями високого рівня та технічних деталей. 2. Андра дуже обізнана про його викладання. 3. Вправа
Steven Wu - Intelligent Medical Objects
Курси: Apache Spark in the Cloud
Machine Translated
Маючи руки на сеансі / завдання
Poornima Chenthamarakshan - Intelligent Medical Objects
Курси: Apache Spark in the Cloud
Machine Translated
Тренер налаштований на тренування, який трохи заснований на запит аудиторії, тому киньте деякі світло на кілька різноманітних тем, які ми просили
Intelligent Medical Objects
Курси: Apache Spark in the Cloud
Machine Translated
Його темп був чудовим. Я любив той факт, що він вступив у теорію так, щоб я зрозумів, чому я зробив би речі, які він запитує.
Intelligent Medical Objects
Курси: Apache Spark in the Cloud
Machine Translated
Я думаю, що тренер був відмінним стилем поєднання гумору і реальних історій життя, щоб предмети на руку дуже доступним. Я дуже рекомендую цей професор в майбутньому.
Курси: Spark for Developers
Machine Translated
Це одна з кращих якість онлайн навчання я коли-небудь прийнятих в моїй 13-річної кар'єри. Слідкуйте за велику роботу!.
Курси: Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP
Machine Translated
Spark Підкатегорії
Spark Зміст курсу
Назва курсу
Тривалість
Огляд
Назва курсу
Тривалість
Огляд
21 годин
Огляд
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 годин
Огляд
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 годин
Огляд
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 годин
Огляд
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 годин
Огляд
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 годин
Огляд
In this instructor-led, live training in україні (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 годин
Огляд
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 годин
Огляд
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 годин
Огляд
This instructor-led, live training in україні (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 годин
Огляд
This instructor-led, live training in україні (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 годин
Огляд
This instructor-led, live training in україні (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 годин
Огляд
This instructor-led, live training in україні (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 годин
Огляд
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 годин
Огляд
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 годин
Огляд
In this instructor-led, live training in україні, 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 годин
Огляд
In this instructor-led, live training in україні, 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.
Інші країни
Консалтинг
Online Apache Spark courses, Weekend Apache Spark courses, Evening Spark training, Spark boot camp, Apache Spark instructor-led, Weekend Spark training, Evening Spark courses, Apache Spark coaching, Apache Spark instructor, Apache Spark trainer, Apache Spark training courses, Spark classes, Spark on-site, Spark private courses, Spark one on one training
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