Training course · AI Agents · Data Analysis & Excel

AI Agents for Data Analysis and Excel

Agentic AI for business teams: understand AI agents, automate workflows safely and keep control with human-in-the-loop and governance.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“AI Agents 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 AI Agents in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Data Analysis & Excel.

AI agents go a step beyond conventional chat assistants: they plan sub-tasks, use tools such as search, files or business applications and complete multi-step work largely on their own. Over two days you will learn how agents are built, how they differ from chatbots and traditional automation, and which tasks genuinely justify their use. Widely used platforms serve as practical examples, including Microsoft Copilot Studio, custom GPTs and Claude with projects and tool connections.

In the hands-on sessions you design agent workflows for tasks from your own area of work, from triaging requests through research and drafting to handing results over to business systems. You decide where a person reviews and approves, which permissions an agent receives and how errors are detected. A dedicated block covers governance, data protection and accountability, so that your agents not only work but remain controllable, traceable and defensible within your organisation.

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 AI agents are structured and clearly distinguish them from chatbots and classic automation.
  • You can select a suitable agent platform for your requirements using transparent criteria.
  • You can design an agent workflow for a real process in your area and build a working prototype.
  • You can define human-in-the-loop checkpoints, test cases and escalation rules.
  • 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

Day 1

Module 1 What makes an AI agent
  • Agent building blocks: language model, instructions, knowledge, tools and memory
  • How agents differ from chatbots, macros and classic workflow automation
  • Levels of autonomy: from suggestion-making assistants to agents that act independently
  • Realistically judging which tasks suit agents and which do not
Module 2 Platform overview: Copilot Studio, GPTs and Claude
  • Microsoft Copilot Studio: agents grounded in company data and connected to Microsoft 365
  • Custom GPTs: configuring instructions, knowledge files and actions
  • Claude with projects, knowledge bases and tool access via the Model Context Protocol
  • Selection criteria: data access, integrations, administration and licensing
Module 3 Designing and building agent workflows
  • Breaking tasks into steps and defining hand-offs between agent and human
  • Writing system instructions, examples and knowledge sources for consistent output
  • Connecting tools: search, documents, email, spreadsheets and business applications
  • Building a prototype agent for a real process from your own area
Module 4 Human-in-the-loop, quality and error handling
  • Setting approval steps, escalation rules and thresholds for human review
  • Test cases, evaluation criteria and spot checks for quality assurance
  • Common failure modes: wrong tool choice, endless loops and fabricated facts
  • Using structured user feedback to improve the agent over time

Day 2

Module 5 Governance, security and roll-out
  • Roles and responsibilities across business units, IT, data protection and works council
  • Least-privilege permissions, logging and protection against prompt injection
  • Positioning under the EU AI Act and GDPR: transparency, documentation and data flows
  • From pilot agent to production: operation, maintenance and measuring success
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

You should already use an AI assistant such as ChatGPT, Copilot or Claude on a regular basis. No programming skills are required. Confident everyday use of Excel; no programming skills required.

Technical requirements

You will need a laptop with an up-to-date browser. Ideally you have access to at least one agent platform such as Copilot Studio, ChatGPT with GPTs or Claude; practice accounts can be provided if needed.

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.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
  • Thu, 10 December 2026 – Fri, 11 December 2026 Salzburg Request
  • Wed, 16 December 2026 – Thu, 17 December 2026 Online Request
  • Tue, 19 January 2027 – Wed, 20 January 2027 Bremen Request
  • Wed, 27 January 2027 – Thu, 28 January 2027 Online Request
  • Mon, 1 February 2027 – Tue, 2 February 2027 Augsburg Request

Frequently asked questions

Do I need programming skills to build AI agents?

No. The platforms used on the course rely on visual interfaces, plain-language instructions and ready-made connectors. You learn to specify agents precisely from a business perspective, connect tools and test workflows. Where deeper technical integration would be needed, you will know which requirements to put to your IT team.

Which platform will we use during the course?

The course is vendor-neutral and uses Microsoft Copilot Studio, custom GPTs and Claude as examples. You build your prototype on the platform that is available or planned in your organisation. The principles of workflow design, control and governance you learn carry over to other agent solutions as well.

How do I stop an agent from acting without control?

Through deliberate design: agents receive only the minimum permissions they need, critical actions such as sending, booking or deleting require human approval, and every step is logged. In addition, you define test cases and escalation rules. These are exactly the control mechanisms you develop for your own use case during the course.

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 “AI Agents for Data Analysis and Excel” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm 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 or Kaiserslautern. We can also run the course exclusively for your team.

More courses for Data Analysis and Excel

More AI Agents courses

All 45 AI Agents courses

AI Agents · MunichAI Agents · SalzburgAI Agents · BerlinAI Agents · AugsburgAI Agents · HanoverAI Agents · BremenAI Agents · StuttgartAI Agents · KaiserslauternAI Agents · Online