Навчальні курси Graph Computing

Навчальні курси Graph Computing

Місцеві навчальні курси з графічних Graph Computing під керівництвом інструкторів демонструють завдяки практичній практиці різні технологічні пропозиції та реалізації для обробки даних графіків з метою виявлення реальних об'єктів, їх характеристик та зв’язків, а потім моделюють ці відносини та обробляють їх як дані, використовуючи підходи графічних обчислень. Навчання Graph Computing доступне як "навчання на місці" або "дистанційне тренування в прямому ефірі". Навчання в прямому ефірі на місці може проводитися локально в приміщеннях замовника в україні або в корпоративних навчальних центрах NobleProg в україні . Дистанційне тренування в прямому ефірі здійснюється за допомогою інтерактивного віддаленого робочого столу. NobleProg - Ваш місцевий провайдер навчання

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Graph Computing Підкатегорії

Graph Computing Зміст курсу

Назва курсу
Тривалість
Огляд
Назва курсу
Тривалість
Огляд
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.
7 годин
Огляд
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 годин
Огляд
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

Audience

- Developers
- Data Engineers

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
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

Audience

- Developers

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.
14 годин
Огляд
This instructor-led, live training in україні (online or onsite) is aimed at technical persons who wish to query RDF data stored in a Semantic Web database.

By the end of this training, participants will be able to:

- Understand the difference between semantic web data and relational data.
- Query public datasets based on Semantic Web standards.
- Model data for querying with SPARQL.
- Transition a website's data to semantic web linked data.
- Run SPARQL queries from within an existing application.
7 годин
Огляд
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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