Data Mining in Practice (PDM)

Target:
The aim of this method course is to learn the practical use of concepts and methods of data mining. The course is designed to be software-independent and cross-sectoral and is also suitable for users who do not work with statistics.

Target group:
This course is aimed at project managers and qualified specialists in service or industrial companies who wish to evaluate their data using data mining.

Course contents:
The course is the practical continuation of the method course "Methods for Statistical Data Mining" (MDM). Using concrete examples, the participants put their theoretical knowledge into practice with modern data mining software. The topics:

  • Exploration / unsupervised learning
    • Which records show similarities?
    • Which data sets form natural groups and structures?
  • Classification / supervised learning
    • Which influencing factors determine affiliation?
    • What conclusions can be drawn from this?
    • Which of the forecast models should be preferred?

We offer this training in cooperation with our partner Statoo Consulting. Trainer is the statistician Dr. Diego Kuonen, CStat PStat CSci, CEO and CAO of Statoo Consulting, lecturer at the University of Geneva and president of the Swiss Society of Statistics. Participants will receive a printed manual in English with all course slides. Upon request, a test license Statistica Data Miner will be made available free of charge for 30 days in order to reproduce what has been learned in your own company.

Prerequisites:
This course requires knowledge from the Methods for Statistical Data Mining (MDM) course. No knowledge of the Statistica Data Miner software is required, as only its self-explanatory, intuitive project interface is used.

Supplementary courses:

For further consolidation, we offer our method courses "Efficient Data Management" (EDM) and "Big Data Analytics" (BDA). For practical implementation, we recommend the product courses "Statistica Introduction" (STE) and "Statistica Data Miner" (SDM).

Duration: 1 day         Time: 8:30 - 16:00 o'clock

 

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