AI Literacy
AI literacy, from AI culture to agentic AI: concepts, limits, prompting, agents, EU AI Act
About AI Literacy Training
A complete, half-day AI literacy training that takes a team from "what is AI, really?" to a clear view of agents and agentic workflows, and turns a legal obligation into a working skill set.
A legal obligation since 2 February 2025. Article 4 of the EU AI Act requires providers and deployers of AI systems to ensure a sufficient level of AI literacy of their staff. Using Copilot, ChatGPT or Claude at work makes your organization a deployer: this training is how you meet that obligation, with skills your teams keep using afterwards.
The eaQbe Methodology: A Progressive Learning Curve
We don't believe in training that overwhelms participants with theory. We believe in structured immersion: every concept enters the room through a story, a demonstration or a quiz before it gets a name, so the session works for every profile, from assistants to executives.
The half-day covers the full arc of modern AI in four movements. It opens with AI culture: where AI comes from, what it is, and what separates intelligence from knowledge. It then opens the machinery: how models learn, what a language model does, and what it cannot do. It confronts the limits: hallucinations, biases, and the rules of responsible use at work, up to the EU AI Act risk taxonomy and a compliance checklist. And it ends where the field is heading: prompting, agents and agentic workflows, closing with a workshop that maps AI opportunities onto the participants' own tasks.
By the end of the session, participants can:
- explain what a model is, how it is trained, and why it answers in probabilities,
- name the structural limits of generative AI and the habits that contain them,
- write and iterate effective prompts, and use AI as their own prompt coach,
- read the agentic landscape: RAG, MCP, agents, agentic workflows and the five levels of autonomy,
- identify where AI belongs in their own work, starting from the problem rather than the technology.
From AI culture to agentic AI: a half-day immersion
A story-driven program in four modules, punctuated by interactive quizzes and live demonstrations.
Module 1 - AI culture: where it comes from, what it is
- Where AI begins: programs, algorithms, and the definition that separates them from AI
- The GPT-3.5 moment and its precedents: Macintosh 1984, Netscape 1994
- Intelligence vs knowledge: the Turing test, the chinese room, Deep Blue vs Kasparov
- Seven decades in one timeline: founding methods, the learning era, big data, GPU
- The AI economy: who builds, who funds, who competes
Module 2 - The machinery: from machine learning to LLMs
- Machine learning: supervised, unsupervised, reinforcement, through everyday analogies
- Training a model: features, weights, error, the optimizer; training vs inference
- Deep learning: layers that build their own features, and why GPUs changed the game
- NLP, the Transformer, tokens and next-word prediction: what an LLM does and does not do
- LLM vs reasoning models (LRM); generative AI vs LLM; reCAPTCHA, or how the world labelled the training data
Module 3 - Limits, risks and responsible use
- Hallucinations: why they are structural, and the courtroom case that made them famous
- Biases and temperature: what they change, and what they do not fix
- Create or repeat: what generative models remix, demonstrated live
- Do and don't at work: approved tools, data classes, audit trail, transparency
- EU AI Act: Article 4, the risk taxonomy, and a compliance checklist for your organisation
Module 4 - Prompting, agents and the agentic workflow
- The anatomy of a good prompt: role, objective, context, tone, constraints
- Prompting as a conversation: iteration, and the AI as your own prompt coach
- From foundation models to agents: RAG, MCP, memory, tools, planning
- The five levels of agentic AI, and agentic workflows: teams of specialised agents
- Workshop: start from the problem, not the technology: task inventory, impact vs effort matrix
Participants leave with a shared vocabulary, the reflexes of responsible use, and a shortlist of AI opportunities mapped on their own work.
Frequently asked questions
Is AI literacy training mandatory for companies in the EU?
Yes, since 2 February 2025. Article 4 of the EU AI Act requires providers and deployers of AI systems to ensure a sufficient level of AI literacy of their staff, and using Copilot, ChatGPT or Claude at work makes your organization a deployer. This half-day training is designed to meet that obligation, and the skills remain useful well beyond compliance.
Do participants need a technical background?
No. The training is built for every profile, from assistants to executives, with no prerequisites. Every concept enters the room through a story, a demonstration or a quiz before it gets a name: participants leave able to explain what a model is without ever having seen a line of code.
What does the half-day cover?
The full arc of modern AI in four movements: where AI comes from and what it is; how machine learning and language models work; their limits, from hallucinations to the EU AI Act risk taxonomy; and where the field is heading, with prompting, agents and agentic workflows. The session closes with a workshop mapping AI opportunities onto the participants' own tasks.
Does it cover AI agents, or only chat assistants?
It goes up to agents. The last module explains RAG, MCP, AI agents and agentic workflows, and the five levels of autonomy, so participants can read the landscape their tools are heading into, not just the chatbot era it started from.
Is the training available in French and English, on-site or remote?
Both languages, and both formats. Sessions run on-site across Belgium and Luxembourg (we are based in Brussels) or remotely for teams across the EU, in small groups.
How is this different from an e-learning module?
It is live, scenario-driven and taught by practitioners who build and run agentic AI systems in production. Game-show quizzes keep every profile engaged, the examples come from real deployments, and the closing workshop produces a shortlist of AI opportunities specific to your organisation, which no generic module can do.
What makes eaQbe's trainings right for your team ?
Scenario-based learning
Our training bridges the gap between concepts and reality. We immerse participants in realistic business scenarios, ensuring skills are directly applicable to your specific challenges.
Trainings led by experts
Our trainers are data science specialists with solid teaching experience. They make complex topics accessible through a clear, structured approach focused on practical application
Progressive autonomy & mastery
Each participant is guided step by step in their learning journey: from theory and demonstrations to guided exercises, leading to full autonomy.