AI Fundamentals

What can generative AI do at work, and what can't it?

1250 € per session, excl. VAT

In short

Gain the clarity and confidence to use generative AI effectively and safely at work. This course provides a solid, tool-independent foundation, explaining what large language models do, their common pitfalls like hallucinations and bias, and crucial confidentiality rules. Learn to identify when AI is the right tool and when it's not.

Why this training?

As the foundational pillar of our AI Academy, this course is the recommended learning prerequisite for the specialised training, unless you have equivalent experience. It establishes a shared baseline of knowledge, so that every participant in subsequent courses shares a common, accurate understanding of generative AI's core mechanics and risks. We focus on building a 'tool-agnostic' mindset, moving beyond specific product features to grasp the universal principles of how these models work. This shared foundation is crucial for creating a secure and efficient AI-powered work environment and for progressing to more advanced applications with a solid risk-awareness framework in place. The hands-on portion of the course involves practical, interactive exercises using the AI assistant specifically authorised by your organisation. Participants will work with fictional data to explore the model's capabilities and limitations in a controlled environment. Activities include prompting the AI, critically evaluating its output for common errors like hallucinations and bias, and applying a checklist-based verification process. This approach ensures that the learning is directly applicable within your company's existing toolset and security guidelines. Deliverables: A reference guide summarizing key concepts, risks, and best practices.; Checklists for evaluating AI responses and ensuring data confidentiality.; Access to a framework for deciding when and when not to use generative AI.. This course is tool-independent and does not teach specific features of any single AI product, as these can vary by plan or administrator settings. It provides foundational concepts, not a guide to advanced 'prompt engineering' or a guarantee of specific productivity gains. The workshop is delivered in person as a private session for up to 12 participants, in one language chosen from French, Dutch and English. All exercise data is fictional or anonymised, and every result produced with AI is reviewed and validated by a responsible person. The aim is a bounded result the team can reuse, not a promise of deployment.

Objectives of this training

  • Explain how a large language model generates responses based on patterns, not facts.
  • Identify typical AI errors such as hallucination, outdated information, and bias.
  • Apply strict confidentiality rules by knowing what data never to paste into an AI tool.
  • Implement internal organisation rules for safe and compliant AI usage.
  • Develop verification habits to critically assess AI-generated content before use.

Who is it for and what are the prerequisites?

Roles and tasks concerned

  • Any professional curious about using generative AI tools in their daily work.
  • Teams looking to establish a common understanding and safe usage guidelines for AI.
  • Managers who need to grasp the fundamentals to guide their teams effectively.

Prior skills

  • No prior knowledge of artificial intelligence is required. No subscription is needed for the theory part of the course. For the hands-on exercises, participants will use an AI assistant that their organisation authorises, using their real accounts and access rights. A paid plan is only necessary if the organisation's chosen tool requires it. All exercises will use fictional data to ensure confidentiality.

What you will work on

  1. What is a Large Language Model (LLM)?

    Understanding prediction vs. knowledge How training data shapes AI responses

  2. Recognising Common AI Pitfalls

    The concept of 'hallucination' and fabricated information Detecting outdated information and inherent biases

  3. Confidentiality and Data Security

    What constitutes sensitive or confidential data Company policies and rules for AI usage

  4. Practical Application and Verification

    When to use AI and when to rely on human expertise Habits for verifying AI-generated content

What you take away

  • A reference guide summarizing key concepts, risks, and best practices.
  • Checklists for evaluating AI responses and ensuring data confidentiality.
  • Access to a framework for deciding when and when not to use generative AI.

Method and assessment

  • Interactive presentations combining theory and real-world examples.
  • Hands-on exercises using the organisation's authorised AI tool.
  • Group discussions and peer-to-peer learning in a small group setting.

Continuous assessment through participation in exercises and group discussions, culminating in a final case study where participants identify risks and propose a safe workflow.

Frequently asked questions

What concrete result does this course deliver?

Empower your team with the essential knowledge to use generative AI responsibly, minimizing risks while laying the groundwork for safe innovation. Deliverables: a reference guide summarizing key concepts, risks, and best practices., checklists for evaluating ai responses and ensuring data confidentiality., access to a framework for deciding when and when not to use generative ai..

Who is this course for and what are the prerequisites?

It is designed for: any professional curious about using generative ai tools in their daily work., teams looking to establish a common understanding and safe usage guidelines for ai., managers who need to grasp the fundamentals to guide their teams effectively.. No prior knowledge of artificial intelligence is required. No subscription is needed for the theory part of the course. For the hands-on exercises, participants will use an AI assistant that their organisation authorises, using their real accounts and access rights. A paid plan is only necessary if the organisation's chosen tool requires it. All exercises will use fictional data to ensure confidentiality.

What data and access need to be arranged?

Participants must have active accounts for the AI assistant authorised by their organisation before the session begins. Required tools and licences are checked before the session; no subscription is included in the price.

What practical exercise is completed?

The hands-on portion of the course involves practical, interactive exercises using the AI assistant specifically authorised by your organisation. Participants will work with fictional data to explore the model's capabilities and limitations in a controlled environment. Activities include prompting the AI, critically evaluating its output for common errors like hallucinations and bias, and applying a checklist-based verification process. This approach ensures that the learning is directly applicable within your company's existing toolset and security guidelines.

What are the limits and who validates the results?

This course is tool-independent and does not teach specific features of any single AI product, as these can vary by plan or administrator settings. It provides foundational concepts, not a guide to advanced 'prompt engineering' or a guarantee of specific productivity gains.

Can the course be adapted to our line of work?

The in-person session allows for direct adaptation. Exercises and discussions can be tailored to the specific context, roles, and internal rules of the participating organisation, ensuring maximum relevance for the team.

How is the session organised and what does it cost?

Half-day, private in-person session for up to 12 participants. The fee is €1,250 excluding VAT per session. Date and location are agreed during scoping; each session runs in a single language: French, Dutch or English.

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