Training course · Vibe Coding · Data Analysis & Excel
Vibe Coding for Data Analysis and Excel
Build software in natural language: from prompt to app, rapid iteration, quality and security checks, and turning prototypes into production.
- 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
“Vibe Coding 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 Vibe Coding in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Data Analysis & Excel.
Vibe coding lets business users without any programming knowledge build digital tools of their own. You describe in everyday language what a mini app, dashboard or form should do, and tools such as Lovable, Claude, ChatGPT Canvas or Replit generate a working solution. Helpers for your daily work can take shape quickly, without waiting for IT to free up capacity. This course shows you step by step how to make it work, which habits lead to good results, and what really matters along the way.
During the course you build applications drawn from your own work: a KPI overview, a data entry form, a small calculator or an automation for recurring chores. At the same time you learn to assess the risks realistically. Which data may go into such tools, who will run and maintain the solution, and when must IT be involved? With this knowledge you can create useful solutions that are accepted within the organisation and remain secure and sustainable in the long term.
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 build your own mini apps, dashboards and forms through vibe coding without programming skills.
- You describe requirements clearly enough for AI tools to produce usable solutions.
- You improve your applications step by step and check the results for accuracy.
- You automate simple recurring tasks in your working environment.
- 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 Understanding vibe coding as a business user
- What vibe coding is and what you can achieve without programming skills
- Tools at a glance: Lovable, Claude, ChatGPT Canvas, Replit and similar platforms
- Spotting good candidates for your own tools at work
- Realistic expectations: strengths, limits and common pitfalls
Module 2 Describing and building your own mini app
- Capturing goal, users, inputs and desired outcome in plain words
- Generating a first version and clicking through it together
- Improving look, wording and flow with targeted feedback
- Saving milestones and returning to an earlier version when things go wrong
Module 3 Dashboards, forms and calculators
- Turning Excel or CSV data into an interactive dashboard
- Building entry forms with required fields and plausibility checks
- Creating calculators and decision aids for your team
- Checking results for accuracy with test data and spot checks
Module 4 Automating routine work
- Identifying recurring tasks that lend themselves to automation
- Building simple automations for reports, notifications or file storage
- Discussing connections to existing tools via approved interfaces
- Documenting automations clearly and handing them over to colleagues
Day 2
Module 5 Risks and coordination with IT
- Which data may and may not go into AI tools: data protection and confidentiality
- Managing access rights, sharing settings and public links deliberately
- Avoiding shadow IT: clarifying operation, maintenance and ownership
- Preparing a handover to IT when a solution grows or becomes critical
Module 6 Hands-on project: your own solution for Data Analysis & Excel
- CSV cleaning app – A small web app that reads CSV files, detects duplicates, blank rows and format errors and outputs a cleaned file with a change log.
- KPI dashboard – An internal dashboard that reads monthly exports and displays key metrics interactively with prior-period comparison and RAG logic. Filters by region, team or product simplify analysis.
- Formula explainer – A tool into which a complex Excel formula is pasted and which breaks it down into understandable steps and documents it.
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.
Possible hands-on projects
CSV cleaning app
A small web app that reads CSV files, detects duplicates, blank rows and format errors and outputs a cleaned file with a change log.
KPI dashboard
An internal dashboard that reads monthly exports and displays key metrics interactively with prior-period comparison and RAG logic. Filters by region, team or product simplify analysis.
Formula explainer
A tool into which a complex Excel formula is pasted and which breaks it down into understandable steps and documents it.
Prerequisites
No programming knowledge is required; confident use of a browser, office applications and spreadsheets is enough. Confident everyday use of Excel; no programming skills required.
Technical requirements
Your own laptop with an up-to-date browser, Git and an AI coding tool of your choice, such as an AI editor or coding agent with an active account.
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.
- Mon, 23 November 2026 – Tue, 24 November 2026 Online Request
- Wed, 2 December 2026 – Thu, 3 December 2026 Kaiserslautern Request
- Tue, 8 December 2026 – Wed, 9 December 2026 Online Request
- Thu, 14 January 2027 – Fri, 15 January 2027 Augsburg Request
- Wed, 27 January 2027 – Thu, 28 January 2027 Online Request
- Wed, 10 February 2027 – Thu, 11 February 2027 Salzburg Request
Frequently asked questions
Is vibe coding only suitable for quick prototypes?
Vibe coding shines with prototypes, internal tools and experiments. With the right practices, namely clear specifications, tests, reviews and sound version control, results can also be turned into production-ready applications. The course teaches you to manage that transition deliberately and to recognise early on when rebuilding is the wiser option.
Which tools are used in the course?
The course is vendor-neutral. We work with the main tool categories: AI editors such as Cursor or Windsurf, coding agents such as Claude Code or Codex, and browser-based app builders. You are welcome to use your preferred tool, as the principles of specification, iteration, quality and security apply to all of them.
How should I deal with security risks in generated code?
Generated code often contains typical weaknesses such as hard-coded credentials, missing input validation or overly open interfaces. You learn to check specifically for these patterns, build security requirements into the specification from the start, use automated scanning and require a deliberate human sign-off before every deployment.
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 “Vibe Coding 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.
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- AI Agents for Data Analysis and Excel
- Prompt Engineering for Data Analysis and Excel
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- Make for Data Analysis and Excel
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- Perplexity for Data Analysis and Excel
- Mistral Le Chat for Data Analysis and Excel
- EU AI Act & AI Compliance for Data Analysis and Excel
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