Online or onsite, instructor-led live IBM SPSS Modeler training courses demonstrate through interactive hands-on practice how to use IBM SPSS Modeler to perform data mining and text analytics activities.
IBM SPSS Modeler 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 IBM SPSS Modeler training can be carried out locally on customer premises in Singapore or in NobleProg corporate training centers in Singapore.
IBM SPSS Modeler is also known as SPSS Modeler.
NobleProg -- Your Local Training Provider
Testimonials
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Exercises on time series modeling
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That we have used our own data as examples
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customized, in-house file processing and data analysis
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presentation of technologies
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Willingness to share more
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Doing the exercises. I really enjoyed the practicals.
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Marcin knew exactly what he talking about and had proper hands on in-depth experience with the tools. He had answers to all our questions and made some really strong recommendations that we could start working towards with future projects and uses.
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I thought the training was very thorough and while we covered a lot of material, Martin made ample time for questions and gave good focus to each individual and their different requirements.
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His deep knowledge about the subject
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learning how to use excel properly
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I enjoyed the Excel sheets provided having the exercises with examples. This meant that if Kamil was held up helping other people, I could crack on with the next parts.
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The training materials.
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the trainer was very good and made the training perfect for my needs
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His deep knowledge about the subject
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IBM SPSS Modeler Course Outlines in Singapore
Course Name
Duration
Overview
Course Name
Duration
Overview
14 hours
This instructor-led, live training in Singapore (online or onsite) is aimed at data analysts or anyone who wishes to use SPSS Modeler to perform data mining activities.
By the end of this training, participants will be able to:
- Understand the fundamentals of data mining.
- Learn how to import and assess data quality with the Modeler.
- Develop, deploy, and evaluate data models efficiently.
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