AI OM

Course overview

AI OM includes the core modules AI Level 1 and Online Marketing. The training course combines two independent specialist modules to convey fundamental data-based technologies and their targeted application in digital communication and sales channels. The first module focuses on the functioning of data-driven systems, as the targeted use of AI sustainably optimizes operational processes, analyses, and automations in companies. Through understanding mathematical and logical principles, participants learn how AI-supported tools can be used for text and image generation as well as for complex data models. The module highlights the functioning of generative models to properly control the use of AI in content creation and data preparation. A key focus is on the structured formulation of instructions through prompt engineering to achieve high-quality and tailored results through the targeted use of AI. Additionally, the course addresses the reduction of errors and hallucinations that can occur when using AI. The connection of local language models with external knowledge bases through retrieval-augmented generation is also an important element for the practical use of AI in companies. Another aspect concerns legal regulations such as the EU AI Act and ethical guidelines to ensure the use of AI in accordance with data protection regulations and copyright laws. Practical application of technologies The second module focuses on the practical application of these technologies in contemporary online marketing. The seminar covers the conception, automation, and optimization of data-driven marketing campaigns and content strategies. Finally, quality control of automated content generation is taught to reliably evaluate the outputs of AI systems before publication. Graduates acquire solid foundational knowledge to independently, compliantly, and efficiently implement the use of AI in digital marketing channels. Theoretical and technical foundations The first module conveys the theoretical and technical foundations of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL). Participants learn to distinguish fundamental learning forms such as supervised learning, unsupervised learning, and reinforcement learning for analyzing complex data structures within data mining. A central focus is on the functioning of generative systems, natural language processing (NLP), large language models (LLMs), and the underlying transformer architecture. Participants acquire solid skills in prompt engineering for the targeted generation of texts, codes, and requirement specifications. To ensure high data and result quality, participants learn to recognize hallucinations, avoid overfitting and underfitting, and use embeddings and vector databases for semantic information processing. The training is supplemented by regulatory and ethical questions within the framework of AI ethics & bias, explainable AI (XAI), and the requirements of the EU AI Act in connection…

Upcoming dates

• 2026-11-01T23:00:00.000Z · 2026-12-10T23:00:00.000Z · Nürnberg, Mittelfranken · Combined Learning
• 2026-11-01T23:00:00.000Z · 2026-12-10T23:00:00.000Z · Wiesbaden · Combined Learning
• 2026-11-01T23:00:00.000Z · 2026-12-10T23:00:00.000Z · München · Combined Learning
• 2026-11-01T23:00:00.000Z · 2026-12-10T23:00:00.000Z · Stuttgart · Combined Learning
• 2026-11-01T23:00:00.000Z · 2026-12-10T23:00:00.000Z · Regensburg · Combined Learning