Classroom Training

After only a few hours of in-class training you will understand key machine learning algorithms and be able to apply them to a wide range of problems. No coding, no math - just visualizations and interactive data exploration!

Pick the right course for you

or contact us for a custom-designed course

Data Mining for Business
Text Mining for Social Sciences
Introduction to Data Mining

Why should you attend?

  • You will learn about latest data science and machine learning approaches that specifically address business problems.
  • After completing the course, you will be able to predict churn, segment customers, detect brand sentiment and recommend shopping carts.
  • We will emphasize on intuition. No complex math, statistics, or programming.
  • The course will be hands-on, we will work on examples and do case studies. No boring PowerPoints.

Course content

  • Data exploration and preprocessing.
  • Key statistical analyses through intelligent visualizations.
  • Clustering and customer segmentation.
  • Classification, predictive modeling, and churn prediction.
  • Overfitting, how to do predictions properly. Model scoring end evaluation.
  • Text mining for business, brand monitoring and sentiment analysis.
  • Essentials of image analytics.


  • Two day (5-hours per day) course on data mining and machine learning.
  • Lecture notes (~80 pages) with extra explanations, illustrations and examples.
  • Free software and data sets used during the course.
  • Certificate of attendance.


  • 1600 EUR / 1800 USD per attendee, minimum 5 participants.
  • Contact us for group discounts or off-site courses.


  • No prior knowledge on data science, machine learning, or statistics is required.
  • Bring your own laptop.
Get in touch
Data Mining for Business

“Playing with data is fun. It's like a detective story, where data gives you clues and you dig ever deeper into the mystery until finding the hidden treasure, the cunning murderer, or the mischievous gene.”

Janez Demšar

Janez Demšar, prof. dr.


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