Online or onsite, instructor-led live Graph Computing training courses demonstrate through hands-on practice the various technology offerings and implementations for processing graph data, with the aim to identify real-world objects, their characteristics and relationships, then model these relationships and process them as data using graph computing approaches.
Graph Computing training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Graph Computing training can be carried out locally on customer premises in Oakville or in NobleProg corporate training centers in Oakville.
NobleProg -- Your Local Training Provider
Oakville - Winston Park
2010 Winston Park Drive, Oakville, Canada, L6H 5R7
The Winston Park centre is located close to both the Queen Elizabeth Way and Ontario 403 giving easy access for Burlington and Hamilton to the west and Mississauga and Toronto to the East.
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.
In this instructor-led, live training in Oakville, 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.
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.
This instructor-led, live training in Oakville (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.
Online Graph Computing training in Oakville, Graph Computing training courses in Oakville, Weekend Graph Computing courses in Oakville, Evening Graph Computing training in Oakville, Graph Computing instructor-led in Oakville, Weekend Graph Computing training in Oakville, Graph Computing boot camp in Oakville, Graph Computing classes in Oakville, Graph Computing coaching in Oakville, Graph Computing one on one training in Oakville, Graph Computing trainer in Oakville, Graph Computing private courses in Oakville, Graph Computing on-site in Oakville, Evening Graph Computing courses in Oakville, Online Graph Computing training in Oakville, Graph Computing instructor in Oakville, Graph Computing instructor-led in Oakville
