AI LDR

Course overview

AI LDR includes the core modules AI Level 1 and Leadership. Fundamentals of Modern Data Processing Systems The training course imparts the fundamentals of modern data processing systems as well as the strategic linking of future-oriented leadership concepts through the targeted use of AI in corporate management. The focus is on understanding basic system architectures, as the use of AI sustainably optimizes administrative leadership processes, decision-making, and organizational structures. By working on technical principles, participants learn how AI-supported systems contribute to structuring complex management information. The seminar highlights the functioning of language and data processing systems to properly manage the use of AI in automating information flows and analysis models. A key emphasis is on the precise formulation of instructions to generate high-quality and reliable foundations for strategic decisions through the use of AI. Furthermore, the course addresses the recognition of logical errors and hallucinations that can occur when using AI in trend analyses or performance evaluations. Connecting external data sources with AI models is also an important element for the reliable provision of corporate data in the leadership context. Another aspect concerns data protection regulations under the EU AI Act and ethical guidelines to ensure the use of AI is in line with corporate compliance standards. Finally, quality control of automated analyses is addressed to anchor the use of AI in modern leadership cultures in a compliant and sustainable manner. Graduates acquire solid expertise to methodically and purposefully manage data-driven transformation processes involving modern AI systems. Theoretical and Technical Foundations The course 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 the framework of 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, requirement specifications, and structured data. Additionally, the course covers advanced techniques such as Retrieval-Augmented Generation (RAG) for integrating internal corporate knowledge bases and methods for fine-tuning pre-trained models. 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 technical training is complemented by regulatory and ethical questions within the framework of AI Ethics & Bias, Explainable AI (XAI), and the requirements of the…

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 · München · Combined Learning