Online or onsite, instructor-led live GraphX training courses demonstrate through hands-on practice how to implement GraphX to carry out graph computing across many machines in parallel.
GraphX 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 GraphX training can be carried out locally on customer premises in Amiens or in NobleProg corporate training centers in Amiens.
NobleProg -- Your Local Training Provider
Amiens, City Center
Centre International Jules Vernes, 72 rue des Jacobins, Amiens, france, 80000
Nearest airport to the training center: Roissy Charles-de-Gaulle International Airport
Nearest train station: Amiens train s...
Nearest airport to the training center: Roissy Charles-de-Gaulle International Airport
Nearest train station: Amiens train station
Nearest parking lot to training center: Parking EFFIA Amiens The Jacobins
Nearby cafés, restaurants and bars: Restaurant L'adresse, Restaurant From's bistrot à Fromages, Bar Tower's Pub
Training can also be organized on your premises in Strasbourg or remotely. The 3rd option is to rent a room specifically for the duration of the course.
Training sessions can be given in English or French. For each session, we organize a coordination call with the trainer and participants to adapt the program to your expectations and level. Training includes theory, discussion, questions/answers and practical exercises.
Remote training is delivered via DaDesktop for training, a software package published by NobleProg that enables participants to have a workstation (VM) set up specifically for the training.
In this instructor-led, live training in Amiens, 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.
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