
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 Luxembourg or in NobleProg corporate training centers in Luxembourg.
NobleProg -- Your Local Training Provider
Testimonials
Broad coverage and deep knowledge about Semantic Web
XINJIAN GUO - Yale University
Course: Semantic Web Overview
He was interactive
Suraj
Course: Semantic Web Overview
Very nice training
Maira Frisch - Novartis Pharma AG
Course: SPARQL
Graph Computing Subcategories in Luxembourg
Graph Computing Course Outlines in Luxembourg
- 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.
- 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.
- 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.
- 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.
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