* * * Training in GERMAN language! * * *

Identify patterns, trends, and interconnections in networked Systems and learn how to implement AI solutions in the sense of Agentic AI!

Keywords like Artificial Intelligence (AI), Machine Learning, Predictive Analytics, Process Mining, and Chat GPT are currently on everyone's lips. But what exactly are they, and how can these technologies be used profitably in a company?

A key focus of the “Certified Citizen Data Scientist” training is the targeted extraction of valuable knowledge from large datasets. You will learn to systematically analyze data and implement predictive AI solutions. Our focus is on topics in production and development, including efficiency improvements, plant productivity, quality enhancement, and energy optimization.

The goal is to use statistical methods to identify correlations, patterns, and trends and to create mathematical prediction models from them. You will gain an overview of the most common tools and methods in the fields of artificial intelligence, machine learning, and predictive analytics. We will also provide an outlook on the latest possibilities in the field of agentic AI. A comprehensive case study from the field of energy management will accompany the entire training. As a special feature, all participants will receive the workbook "Data Science Innovationen erfolgreich umsetzen" published by Hanser Verlag and authored by successfactory.

Target Group

This training is designed for individuals who want to learn from data, implement mathematical models themselves, and advance data-driven decision-making processes. No programming skills are required, as we work with "no-code tools" like KNIME. We particularly address individuals working in development, production, quality management, and energy management.

Agenda

• Day 1
  Procedural model for implementing data science solutions – CRISP-DS (cross industry standard process for data science), basic concepts of AI and machine learning, introduction and basics KNIME for predictive analytics, energy management as a use case
• Day 2
  Find and describe use cases and business cases, analyze data, improve data quality, collect the correct data (feature engineering)
• Day 3
  Train prediction models, overview of the most important algorithms in the field of clustering, regression, classification including introduction to neuronal networks and reinforcement learning (use of software solutions like Orange)
• Tag 4
  Evaluate prediction models, choose the right splitting strategy, hyperparameter tuning und selecting the right model
• Tag 5
  Validate and implement solutions, productive implementation of solutions and build trust, surveillance and retraining, outlook to configuration of AI-agents (use of LLMs like GPT and software solutions like n8n)

Organizational Matters

• Date: 5-day seminar from 8th to 12th of June, 2026
• Venue: University of Leoben, Chair WBW, Peter-Tunner-Straße 25-27 (3rd floor)
• Language: Training in GERMAN language
• Participation fee: EUR 3.490,- normal price  /  EUR 3.190,- early bird until 9th of March  /  optional EUR 350,- Certification