Online or onsite, instructor-led live Unsupervised Learning training courses demonstrate through interactive hands-on practice how to use unsupervised machine learning techniques to discover patterns, group data, and extract meaningful insights from unlabeled datasets.
Unsupervised Learning 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 Unsupervised Learning training can be carried out locally on customer premises in Graz or in NobleProg corporate training centers in Graz.
Unsupervised Learning is also known as Unsupervised Machine Learning.
NobleProg -- Your Local Training Provider
NobleProg Graz
Waagner-Biro-Strasse 47, Graz, Austria, 8020
Overview
Our training facilities are located at Waagner-Biro-Strasse 47 in Graz. Our spacious training rooms are located directly in the old town and offer optimal training conditions for your needs.
Directions
The NobleProg training facilities are best reached via the A9 motorway and the federal highway 67.
Parking spaces
There are parking spaces in the streets around our training rooms as well as the ContiPark multi-storey car park.
Local infrastructure
There are numerous restaurants in the downtown area and hotels are also within walking distance.
This instructor-led, live training in Graz (online or onsite) is aimed at beginner to intermediate-level data analysts and data scientists who wish to use Weka to perform data mining tasks.
By the end of this training, participants will be able to:
This instructor-led, live training in Graz (online or onsite) is aimed at engineers, data scientists, and data analysts who wish to use Dataiku DSS for the development of machine learning pipelines, and leverage AI processes in generating strategic organizational initiatives.
By the end of this training, participants will be able to:
Install and configure Dataiku DSS upon their preferred operating system.
Understand AI/ML concepts and principles that are fundamental to Dataiku features.
Create and implement their own data visualization codes in Dataiku DSS projects.
Deploy ML models and pipelines into production environments built around Dataiku DSS.
Optimize the agility and flexibility of data analysis methods of their enterprise applications.
Utilize Dataiku DSS to secure and manage how data flows through further business systems.
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