AI Literacy Course

What is artificial intelligence? The EU AI Act definition, the difference between machine learning and generative AI, and risks such as bias and hallucinations.

The four risk classes of the EU AI Act, prohibited practices, provider vs. deployer obligations, and the regulatory timeline.

Prohibited AI practices under Art. 5 EU AI Act: emotion recognition at work, social scoring, biometric categorization. Deepfakes and permitted use cases.

AI transparency obligations: labeling AI-generated content, human oversight, building an AI inventory and documentation duties.

Data protection and GDPR for AI systems: data protection impact assessments (DPIA), data processing agreements, legal bases and data subject rights.

Practical AI tools: ChatGPT, Copilot and DeepL in everyday work. Detecting shadow AI, prompting with the CRAFT method, quality assurance.

Liability and compliance in AI: the liability cascade, Art. 4 evidence, incident reporting, fines and sanctions under the EU AI Act and GDPR.

AI governance in the enterprise: AI officer, AI policy, approval processes, monitoring and audits — the organization behind AI use.

How companies develop an AI strategy, calculate ROI and set up an AI policy — including a template.

Advanced prompting techniques, RAG patterns and the targeted use of AI agents in a business context.

How companies prepare for an AI audit, build complete documentation and establish incident response processes.

How companies anchor AI literacy as a culture, coach employees and lead change processes successfully.

When do you use LLMs (brain) and when workflows (muscles)? Cost-benefit analysis, the ROI of AI automation and the 80/20 rule for efficient AI strategies.

How much energy does AI use? Green AI, AI costs and efficient model usage — practical levers for sustainable AI in the company.

How to measure your organization's AI maturity, prepare audits under the EU AI Act, and close the gaps between the current state and legal requirements.

How to steer, measure and monetize AI initiatives across the organization — from governance structure to the ROI metric.

Where bias enters AI systems, why it becomes a business risk, and how a bias audit with fairness checks protects you before go-live.