Training course – EU AI Act & AI Compliance – Data Analysis & Excel

EU AI Act & AI Compliance for Data Analysis and Excel

Putting the EU AI Act into practice: risk categories, deployer obligations, AI literacy under Art. 4, AI policy and GDPR interfaces.

Duration
6 hours, one session
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“EU AI Act & AI Compliance for Data Analysis and Excel” is a hands-on course for roles such as Business users who work regularly with Excel and reports, Controllers and finance staff and Sales and marketing analysts. Rather than learning EU AI Act & AI Compliance in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Data Analysis & Excel.

The EU AI Act is the first comprehensive legal framework for artificial intelligence, and it applies not only to providers but also to organisations that use AI systems in their daily work. In this compact course you will learn how the regulation is structured: prohibited practices, high-risk systems, transparency obligations and general-purpose AI models. You will find out which role your organisation plays as a deployer, which obligations follow and how to record and classify the AI applications you use in a structured way.

The practical part turns the requirements into manageable steps. You clarify what the AI literacy obligation under Article 4 means in concrete terms, how to organise training in a verifiable way and what an internal AI policy should cover. You also examine the interfaces with the GDPR, such as legal bases, data protection impact assessments and automated decision-making. You leave with an AI inventory template, a draft policy and a clear compliance roadmap for your area of work.

In almost every department, decisions are made on the basis of spreadsheets, exports and reports – and much working time goes into cleaning, combining and analysing that data. Generative AI dramatically lowers the barrier to sophisticated analysis. It explains and writes Excel formulas, builds Power Query steps and macros, suggests pivot analyses and charts, generates Python or SQL code for larger datasets and drafts commentary on KPIs. AI agents can prepare recurring reports automatically. This empowers business users to answer questions themselves that once meant waiting for IT or an analytics team. What remains essential is checking results rigorously and keeping an eye on data quality.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Business users who work regularly with Excel and reports
  • Controllers and finance staff
  • Sales and marketing analysts
  • Business analysts and reporting teams
  • Team leads responsible for KPIs

Typical challenges we address

  • Time-consuming manual data cleaning and copy-and-paste processes
  • Complex formulas and macros that only a few people understand
  • Data from different systems in inconsistent formats
  • Error-prone spreadsheets without traceable calculation logic

What you will be able to do

  • You can explain how the EU AI Act is structured and assign your organisation to the correct roles.
  • You can classify the AI applications in use by risk category and maintain an AI inventory.
  • You can name the specific obligations of deployers and derive appropriate measures.
  • You can develop an AI literacy concept under Article 4 and a draft internal AI policy.
  • Create and understand complex Excel formulas, Power Query steps and macros with AI.
  • Clean, analyse and visualise data faster and more transparently with AI support.
  • Automate recurring reports and check AI results methodically for accuracy.

Course outline

Module 1 Structure and logic of the EU AI Act
  • Objectives, scope and phased application of the regulation
  • Roles at a glance: provider, deployer, importer and distributor
  • The risk-based approach: prohibited practices, high risk, limited risk and minimal risk
  • Specific rules for general-purpose AI models
Module 2 Classifying risk in practice
  • Prohibited practices such as social scoring or emotion recognition in the workplace
  • High-risk areas under Annex III, including recruitment, creditworthiness and education
  • Transparency obligations for chatbots, synthetic content and deepfakes
  • Recording and classifying your own AI applications in an AI inventory
Module 3 Obligations for deployers of AI systems
  • Use in line with instructions and human oversight by competent staff
  • Input data quality, monitoring of operation and retention of logs
  • Informing employees and affected persons and reporting serious incidents
  • Fundamental rights impact assessment: when it is required and how it works
Module 4 AI literacy under Art. 4 and internal AI policy
  • What sufficient AI literacy means for different roles
  • Designing training concepts and documenting measures verifiably
  • Components of an AI policy: approved tools, data classes, approvals and labelling
  • Responsibilities, AI officers and involving the works council and IT
Module 5 GDPR interfaces and governance
  • Legal bases, purpose limitation and data minimisation when using AI
  • Data protection impact assessment and its relationship to the fundamental rights assessment
  • Automated individual decisions, data subject rights and data processing agreements
  • Compliance roadmap: priorities, ownership and regular review
Module 6 Practice lab: Data Analysis & Excel
  • Writing and explaining formulas
  • Cleaning and combining data
  • Analyses and charts
  • Python and SQL for large datasets
  • Commenting on KPIs
  • Automating reports
Module 7 Data protection, quality & transfer to daily work
  • Spreadsheets often contain personal data about customers or employees as well as confidential business figures, which may only be processed in approved AI environments and ideally anonymised or aggregated. Analyses relating to employees may be subject to works council rights, and responsibility for the accuracy of reports remains with the business unit.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Writing and explaining formulas

AI creates formulas such as XLOOKUP, SUMIFS or dynamic arrays from a plain-language description and explains existing nested formulas step by step. Common pitfalls are pointed out as well.

Cleaning and combining data

For inconsistent exports, AI suggests cleaning steps, builds Power Query queries or scripts for merging, de-duplicating and normalising, and documents the transformations. The steps can be repeated with one click next time.

Analyses and charts

From a business question, AI derives suitable pivot tables, metrics and chart types and helps present results clearly and accurately. Misleading displays such as truncated axes are avoided.

Python and SQL for large datasets

When Excel reaches its limits, AI generates Python or SQL code for analysing larger datasets, which business users run, understand and adapt step by step.

Commenting on KPIs

Variances, trends and anomalies in reports are translated into clear written commentary for management and departments; hypotheses about causes are checked by experts. Reports become self-explanatory in meetings.

Automating reports

Recurring monthly or weekly reports are automated with macros, scripts or AI agents so that data is retrieved, prepared and distributed as a report. Manual steps and transfer errors largely disappear.

Prerequisites

No legal background is required. A basic knowledge of the GDPR and an overview of the AI applications used or planned in your area are helpful. Confident everyday use of Excel; no programming skills required.

Technical requirements

All you need is a laptop with an up-to-date browser and an office suite for working with templates. No special AI licences are necessary.

Data protection & compliance

Spreadsheets often contain personal data about customers or employees as well as confidential business figures, which may only be processed in approved AI environments and ideally anonymised or aggregated. Analyses relating to employees may be subject to works council rights, and responsibility for the accuracy of reports remains with the business unit.

Dates & locations

For every location we suggest a date roughly four weeks ahead. Your preferred date is always possible.

  • Munich Thu, 10 December 2026 6 hrs Request
  • Salzburg Mon, 14 December 2026 6 hrs Request
  • Berlin Mon, 14 December 2026 6 hrs Request
  • Augsburg Mon, 14 December 2026 6 hrs Request
  • Hanover Fri, 11 December 2026 6 hrs Request
  • Bremen Fri, 11 December 2026 6 hrs Request
  • Stuttgart Thu, 10 December 2026 6 hrs Request
  • Kaiserslautern Mon, 14 December 2026 6 hrs Request
  • Online Wed, 16 December 2026 6 hrs Request

Frequently asked questions

Does the EU AI Act apply to companies that only use AI tools?

Yes. Anyone using AI systems under their own authority in a professional context is a deployer. All deployers must, in particular, ensure that their staff have sufficient AI literacy. Where high-risk systems are used, for example in recruitment, further obligations apply, such as human oversight, logging and informing the people affected.

Does this course satisfy the training obligation under Article 4?

The course covers core AI literacy content and you receive a certificate of attendance that you can add to your documentation. However, Article 4 requires measures tailored to role, prior knowledge and context of use. That is why you also learn how to set up and maintain your own AI literacy concept for your organisation.

Does the course replace legal advice?

No. The training provides practical knowledge for specialists and managers so they can interpret requirements, ask precise questions and implement first measures. For binding assessments of individual systems, especially in high-risk areas, you should involve your legal department, your data protection officer or external specialist lawyers.

Do I need programming skills for data analysis with AI?

No. Good Excel skills are enough to start. AI generates formulas, Power Query steps and, where needed, Python code that you learn to follow step by step. What matters is being able to sanity-check results. The course focuses on exactly these checking techniques alongside hands-on practice.

How reliable are AI-generated formulas and analyses?

Often very good, but not flawless: references, edge cases or wrong assumptions about the data structure lead to silent errors. That is why you verify results with spot checks, control totals and cross-calculations. The course teaches a simple checking routine to apply to every AI-assisted analysis.

How much does “EU AI Act & AI Compliance for Data Analysis and Excel” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 6 hours of live training with a trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. For every location we suggest a date roughly four weeks ahead. In the request form you can always describe your preferred date or period in free text – we check availability and get back to you within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run the course exclusively for your team.

Can the course be tailored to our team?

Yes. Tailor-made courses cost approx. €4,500 more, depending on the topic and by arrangement. We agree content, examples and exercises with you in advance.

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