Online or onsite, instructor-led live RapidMiner training courses demonstrate through interactive hands-on practice how to use RapidMiner Studio for data preparation, machine learning, and predictive model deployment.
RapidMiner 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 RapidMiner training can be carried out locally on customer premises in Innsbruck or in NobleProg corporate training centers in Innsbruck.
NobleProg -- Your Local Training Provider
NobleProg Innsbruck
Valiergasse 58, Innsbruck, Austria, 6020
Overview
Our training facilities are located at Valiergasse 58 in Innsbruck and offer optimal training conditions for your needs.
Directions
The NobleProg training facilities are conveniently located near the main train station, the A12 and A13 motorways are easily accessible.
Parking spaces
There are parking spaces in the surrounding streets around our training rooms.
Local infrastructure
There are numerous restaurants in the downtown area and hotels are also within walking distance.
This instructor-led, live training in Innsbruck (online or onsite) is aimed at intermediate-level data analysts who wish to learn how to use RapidMiner to estimate and project values and utilize analytical tools for time series forecasting.
By the end of this training, participants will be able to:
Learn to apply the CRISP-DM methodology, select appropriate machine learning algorithms, and enhance model construction and performance.
Use RapidMiner to estimate and project values, and utilize analytical tools for time series forecasting.
RapidMiner is an open source data science software platform for rapid application prototyping and development. It includes an integrated environment for data preparation, machine learning, deep learning, text mining, and predictive analytics.
In this instructor-led, live training, participants will learn how to use RapidMiner Studio for data preparation, machine learning, and predictive model deployment.
By the end of this training, participants will be able to:
Install and configure RapidMiner
Prepare and visualize data with RapidMiner
Validate machine learning models
Mashup data and create predictive models
Operationalize predictive analytics within a business process
Troubleshoot and optimize RapidMiner
Audience
Data scientists
Engineers
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.
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