Prompting AI: Fundamentals and Machine Learning

Course overview

Prompting + Machine Learning + Artificial Intelligence + Data Analysis This training course provides knowledge in the application of prompting techniques for various AI models and their integration into machine learning processes. Participants will learn to use data-driven models and automate processes in a business context. Module 1: Fundamentals of Prompting for AI Models Module 2: Differences and Applications of GPT and LLM Prompting Module 3: Introduction to AI, Data Analysis, and Language Models Module 4: Introduction to Machine Learning and AI-Driven Data Analysis Module 5: Analysis Models with Machine Learning and Python !Fundamentals of Prompting for AI Models *Introduction to Prompting: Structure and functionality of text-based inputs for AI models and Large Language Models (LLMs). *Prompting with GPT Systems: Application of GPT prompting and AI prompting for text generation, analysis, and query control. *Application in the AI Context: Use of prompting techniques for machine learning and automated interaction with artificial intelligence. *German Language Prompting: Use of German prompting in LLM prompting and practical exercises for AI communication. !Differences and Applications of GPT and LLM Prompting *Prompting in Comparison: Structure, syntax, and functions of GPT prompting and LLM prompting in the context of artificial intelligence. *Application Areas in AI: Use of GPT prompting and LLM techniques to control text outputs and model behavior. *Practical Prompting: Use of AI prompting for generation, automation, and data processing in AI systems. *Positioning in the ML Environment: Role of prompting in conjunction with machine learning and language model architectures. !Introduction to AI, Data Analysis, and Language Models *Automation and Digitalization: Role of artificial intelligence in companies, smart work, and digitalization in Office 4.0. *Working with Data: Introduction to machine learning with Python, big data concepts, data analysis methods, and neural networks. *AI Applications in Business: Overview of tools, providers, use of Microsoft Copilot, and challenges in everyday work. *Prompting with Language Models: Techniques of GPT prompting, learning AI prompting, application in work organization and office processes. !Introduction to Machine Learning and AI-Driven Data Analysis *Fundamentals of Machine Learning: Introduction to AI, learning algorithms, data analysis methods, and application areas in the business context. *Working with Python: Use of libraries like Scikit-learn for machine learning in Python and initial modeling steps. *From Data to Predictions: Data preparation, feature engineering, model training, and evaluation with big data and statistical tools. *Understanding AI Applications: Use of AI automation, prompting techniques, and Power BI AI functions for analysis optimization. !Analysis Models with Machine Learning and Python *Fundamentals of Machine Learning: Application of data-driven learning models with…

Upcoming dates

• 2026-08-09T22:00:00.000Z · 2026-10-17T22:00:00.000Z · München · Hybrid Learning
• 2026-08-09T22:00:00.000Z · 2026-10-17T22:00:00.000Z · Aachen · Hybrid Learning
• 2026-08-09T22:00:00.000Z · 2026-10-17T22:00:00.000Z · Berlin · Hybrid Learning
• 2026-08-09T22:00:00.000Z · 2026-10-17T22:00:00.000Z · Berlin · Hybrid Learning
• 2026-08-09T22:00:00.000Z · 2026-10-17T22:00:00.000Z · Berlin · Hybrid Learning