Local instructor-led live Graph Computing training courses in България.
Oтзиви от потребители
Много хубаво обучение
Maira Frisch - Novartis Pharma AG
Course: SPARQL
Machine Translated
Graph Computing Subcategories
Graph Computing Course Outlines
Име на Kурса
Продължителност
Общ преглед
Име на Kурса
Продължителност
Общ преглед
28 hours
In this instructor-led, live training in България, 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.
7 hours
The Semantic Web is a collaborative movement led by the World Wide Web Consortium (W3C) that promotes common formats for data on the World Wide Web. The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries.
21 hours
Apache Jena is an open source Java framework for building Semantic Web and Linked Data applications.
In this instructor-led, live training, participants will learn how to use Apache Jena to build and deploy a Semantic Web Application.
By the end of this training, participants will be able to:
- Install and configure Apache Jena
- Convert and store data in RDF format
- Query RDF data using SPARQL
- Test and deploy a semantic web application
- Developers
- Data Engineers
- Part lecture, part discussion, exercises and heavy hands-on practice
- To request a customized training for this course, please contact us to arrange.
21 hours
Blazegraph is an open source, Java-based RDF graph database for storing and representing data with complex relationships. It supports Blueprints and RDF/SPARQL 1.1.
In this instructor-led, live training, participants will learn how to use Blazegraph to capture complex data in graph format for retrieval from a number of sample applications. All exercises will be carried out hands-on in a live-lab environment.
By the end of this training, participants will be able to:
- Install and configure Blazegraph in standalone mode, clustered mode (optional) or embedded mode (optional)
- Create, test and deploy a sample application to query complex data in a Blazegraph data store
- Understand how to leverage GPU (graphics processing unit) to accelerate computations
- Developers
- Part lecture, part discussion, exercises and heavy hands-on practice
- To request a customized training for this course, please contact us to arrange.
14 hours
SPARQL е език за запитване за запитване RDF (Рамка за описание на ресурсите) данни. Това е подобно на SQL за относителни данни в бази данни.
Това обучение, ръководено от инструктори (онлайн или онлайн) е насочено към технически лица, които искат да поискат RDF данни, съхранявани в Semantic Web база данни.
В края на обучението участниците ще могат да:
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Разберете разликата между семантични уеб данни и относителни данни.
Търсене на публични данни на базата на Semantic Web стандарти.
Модел данни за запитване с SPARQL.
Преминаване на уебсайт's данни към семантични уеб свързани данни.
Извършете SPARQL запитвания от съществуващото приложение.
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Интерактивна лекция и дискусия.
Много упражнения и упражнения.
Изпълнение на ръката в живо лабораторна среда.
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За да поискате персонализирано обучение за този курс, моля, свържете се с нас, за да организирате.
7 hours
MediaWiki is a free and open-source wiki software. This one-day course provides participants with an introduction to Semantic MediaWiki.
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