AI literacy for AI users
An adaptive learning introduction to AI for the modern workplace

Developed by AI experts at the appliedAI Institute for Europe
Learn with real-world workplace scenarios and interactive examples
Personalised learning path that adapts to your knowledge level

Build the AI literacy skills your organisation needs — from understanding how AI works to applying it responsibly and effectively in your daily work. 

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This course in a nutshell

Time:

Approx. 1–4 hours (adaptive — varies depending on learner knowledge level)
Target group:

Professionals and knowledge workers who use or plan to use AI tools in their daily work. Suitable for any industry or role, no technical background required.
Prior knowledge:

No prior AI knowledge required. The course adapts to learners ranging from novice to advanced beginner.
Format:

Two adaptive learning modules on the Area9 Rhapsode platform, combining slideshows, interactive exercises, fill-in-the-blank questions, matching activities, case studies, and open-ended reflection tasks.

After completing the course, you will be able to:

  • Define AI and AI literacy
  • Explain how machine learning and large language models work
  • Recognise the elements of the AI technological landscape (machine learning, deep learning, generative AI, agentic AI)
  • Identify the key principles of trustworthy AI (robustness, ethics, lawfulness)
  • Explain the basic purpose and approach of the AI Act
  • Identify workplace tasks where AI assistance is appropriate and where it is not
  • Choose the most suitable AI mode and model for a given task considering cost, speed, and quality
  • Apply prompt engineering principles to get better AI outputs
  • Assess security risks in data scenarios involving AI use
  • Apply a systematic quality control procedure to AI-assisted work
  • Detect and mitigate bias in AI-generated content
  • Evaluate when, how, and to whom AI use should be disclosed in a professional context
  • Demonstrate ownership and responsibility for AI-generated outputs

Syllabus

01 What is AI literacy? Introduction to the concept of AI literacy as defined by the AI Act (Article 4), including why it matters for organisations and individuals. Learners identify its key elements and understand who is obligated to ensure it.

02 What is AI? Exploration of the definition and historical development of artificial intelligence, from its origins as a theoretical concept in the 1950s to today's universally accessible tools like ChatGPT. Includes the AI Act's official definition of an AI system.

03 How AI works An accessible explanation of how machine learning works — from data and algorithms to trained models and inference. Covers how large language models (LLMs) generate text through statistical pattern recognition, illustrated with practical examples.

04 Trustworthy AI principles Introduction to the three pillars of trustworthy AI — robustness, ethics, and lawfulness — and why embedding these from the start matters. Includes the business value of trustworthy AI in terms of market advantage, operational excellence, and long-term sustainability.

05 The AI Act Overview of the world's first comprehensive AI regulation: its purpose, scope, and risk-based classification approach. Learners explore the four risk categories (unacceptable, high, transparency obligations, and low risk) and how trustworthy AI principles are operationalised through legal requirements.

01 Understanding AI capabilities and limitations Learners identify workplace tasks that utilise AI's strengths, recognise when AI assistance is and is not appropriate, and learn how to effectively combine AI use with human expertise. Includes selecting the right AI mode and model based on cost, speed, and quality trade-offs, as well as understanding the types and causes of AI content limitations and how to validate outputs.

02 Effective AI communication Practical prompt engineering skills: how to reconstruct prompts and context to improve outputs, apply six essential principles for writing specific instructions, and break down complex professional tasks into subtasks that can be effectively delegated to AI systems.

03 Trustworthy AI application Applied responsible AI skills for the workplace: assessing data security risks, implementing quality control procedures for AI-assisted work, handling AI mistakes and failures, detecting and mitigating bias in AI outputs, navigating disclosure and documentation requirements, and demonstrating professional ownership of AI-generated content.

Contact us

For more information or to be added to the waiting list, contact us at learn@appliedai-institute.de.