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DTSTAMP:20260813T075945Z
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SUMMARY:Module 3: Statistical Modeling & Machine Learning
DESCRIPTION:Participants will gain in-depth knowledge of modern data modeling\, be able to effectively integrate ML techniques into their work\, and confidently support data-driven decisions for process improvements. \nKey topics of this module: \n➡ Multivariate methods and classical regression models (refresher) to refresh statistical basics.\n➡ Introduction to data orchestration and machine learning – understanding supervised and unsupervised learning.\n➡ Model development using Python\, including data preparation\, feature engineering\, and validation.\n➡ Classification and regression methods such as decision trees\, Naive Bayes or neural networks.\n➡ Differences between classical and ML-based models\, including fields of application and limitations.\n➡ Practical application of ML methods for process optimization\, including visualization and interpretation.\n➡ Confident handling of model quality\, cross-validation and model comparison for well-founded decisions. \n\n\nDates (ONLINE)\nDates (ONLINE)\n– May 4\, 2026. 8:00 a.m. to 5:00 p.m.\n– May 5\, 2026. 8:00 a.m. to 12:30 p.m.\n– May 6\, 2026. 8:00 a.m. to 12:30 p.m.\nDo you have any questions or would you like to participate? We look forward to hearing from you.     \nBecome part of the Data Excellence Experience – we look forward to your participation!\nFurther modules and information: LINK \n_________________________________________________________________________ \n \n  \n  \nYou can find more interesting events related to quality management in the QZ-online.de calendar at\n__________________________________________________________________________
URL:https://www.sixsigmaclub.de/en/event/workshop-statistical-modeling-machine-learning/
LOCATION:ESSC-D Workshop / Training
CATEGORIES:ESSC-D Workshop / Training,Module training
ORGANIZER;CN="European Six Sigma Club Germany e.V.":MAILTO:buero@sixsigmaclub.de
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