We start from the need
Before designing anything we talk: what tools and licenses you have, which processes you want to improve, your team’s level, and which data can be used.
All Solutions
Applied Training
Don't buy courses. Build capabilities with your own data.
We train your team not just to use tools, but to solve real problems inside your organization. Learning by building.
The Madriguera standard
How we train
Every program, whatever the topic, follows the same standard: it is personalized, modular, mostly hands-on, and it always leaves something working in the organization.
On your real work
No toy datasets: practice happens on the organization’s own documents, databases and reports.
More practice than theory
Just the theory you need. Most of the time is spent hands-on in the tool.
There is always a product
Every program ends with something that works: a dashboard, an automated flow, an agent, or a real section of a report.
With judgment
AI proposes; the team analyzes, decides and signs. We teach how to verify sources, protect personal data (Colombian Law 1581 of 2012) and disclose AI use.
Modular
Three blocks. Pick one or stack them.
Training
Builds people’s skills: self-paced exercises, hands-on classes and a bootcamp on your own material.
Solution
Installs the tool and the method: an AI assistant, a dashboard or an automation set up on what the organization already has.
Follow-up
Sustains day-to-day use: follow-up sessions, usage support and adjustments while the team applies what it learned.
A
Training only
Start with people and a good-practice guide.
B
Solution only
Experienced teams who need a shared method.
AB
Training + solution
Learning happens inside the tool, with a pilot as the hands-on case.
ABC
Full path
All of the above, with support while it is applied.
Three formats
Self-paced prepares, classes train, the bootcamp integrates
Self-paced exercises
At your paceShort capsules and challenges with feedback, on the organization’s virtual classroom or ours.
Hands-on classes
In groupsLive sessions, on-site or online: we demonstrate, practice and check together.
Bootcamp
Hands-onAn intensive day in timed rounds, where each team builds and defends a real product.
Four levels
Understand, choose, master, apply
- 01
Understand
How the technology works, what it can and cannot do, and how to use it ethically.
- 02
Choose
Which tool fits each task and what happens to data under each license.
- 03
Master
Converse, delegate and build: the three ways of working with AI and data.
- 04
Apply
Connect the pieces into the team’s own workflow that keeps being used.
Zero long slides. A real product.
Teams of 3 to 5 people work in timed rounds, like a hackathon, on their own material. It can close a program or run on its own for teams that need to get going fast.
Choose and set up
Each team picks the tool and sets up its workspace with its own material.
Converse
The first draft is built with chat. Golden rule: every figure cites its source.
Delegate
An agent consolidates information, builds matrices and prepares annexes.
Red team
Teams swap work and try to “break” it: errors, copying and unsupported figures.
Build and defend
Each team builds its dashboard, flow or agent and defends it before an evaluator.
What makes it different
- Timed rounds, like a hackathon.
- Seeded errors to train a critical eye.
- A red team that audits other teams’ work.
- A quality scoreboard: evidence, verification, originality and own judgment.
What each team leaves with
- A real product, with verified data.
- Its own dashboard, flow or agent.
- A good-practice checklist for using AI and data.
- Feedback from the red team and the evaluator.
AI with judgment
Training and an AI assistant so deans and quality managers build their self-assessment and accreditation reports with AI, without losing analysis or authorship. Eight modules in four levels, a bootcamp on a real accreditation factor, and an assistant set up on the institution’s own AI license that stops where the person has to decide.
- Evidence first: nothing is written without a source.
- Zero figures without a source.
- Take ideas from references, never their wording.
- The quality judgment is human.
AI proposes. The team analyzes, decides and signs.
Certificate with hours
Each participant receives a certificate of attendance with the hours completed, as an informal education program under Colombian Decree 1075 of 2015. It can also be co-certified with the organization’s continuing education unit.
How we start
- 01A conversation to understand the challenge and context.
- 02Choice of blocks, formats and intensity.
- 03Proposal with scope, timeline and price.
- 04Kick-off with the assessment and the first session.
Custom training
We train your team in data and AI, with your own data
Every program is adapted after a short assessment: we pick the level, the examples, and the final deliverable based on your team’s real work. Nothing generic.
AI with judgment for quality reports
For deans and quality managers: self-assessment, program licensing and accreditation with AI support, without losing analysis or authorship. Includes a bootcamp on a real factor and, optionally, an assistant set up on the institution’s license.
Modular: A + B + CHigher education
Generative AI for work teams
ChatGPT, Claude, Gemini, and Copilot applied to each area’s real tasks: writing, analysis, summaries, presentations, and reusable prompts, with clear rules for responsible use.
8 to 16 hoursWhole team
Power BI: from zero to executive dashboards
Power Query, data modeling, DAX, and storytelling. Every participant finishes with a dashboard built on their own area’s data.
16 to 24 hoursAnalysts and coordinators
Python for data analysis
Pandas, visualization, and report automation. From the spreadsheet rebuilt every month to a script that produces it on its own.
20 hoursAnalysts
Automation with n8n + AI
No-code flows that connect email, spreadsheets, and systems, with AI to read, classify, and write. You leave with your own working flow.
12 hoursOperations teams
Data literacy for leaders
Read indicators without being fooled, ask a dashboard the right questions, and decide with evidence. No jargon.
4 to 8 hoursLeaders and committees
Indicators and impact evaluation
Theory of change, logical framework, SMART indicators, and evaluation designs, applied to one of the organization’s real programs.
16 hoursPlanning and M&E teams
Analytics for higher education
Retention, SNIES, ICFES, and accreditation evidence: turning institutional data into alerts and decisions.
12 hoursAcademic and planning offices
Need something different?
We design the program around your challenge: tools, level, and duration.
On-site at your organization
Live online
Groups of up to 20 people
Bootcamp, workshop, or mentoring
Service portfolio
Full portfolio See prototypes
1 working prototypes with simulated data. Open any of them to see its full sheet.
Signs you need this
- Your team takes courses on Coursera/Udemy but nothing changes at work.
- You have Tableau or PowerBI licenses that no one uses properly.
- You depend entirely on external consultants for basic data extraction.
- There is fear or resistance to adopting AI or automation.
Before
Unmotivated staff who see technology as a threat, and generic training with toy datasets ("Titanic" or "Superstore").
After
An empowered team that knows how to ask data the right questions and built its first dashboard during the workshop, using the company’s own data.
What we build
Hybrid learning paths (in person/remote) designed entirely around your area’s strategic challenges.
What you get
Real capability transfer, course materials, and the products (dashboards, scripts) your own employees build during the program.
What we need
Leadership commitment to free up people’s time, and permission to use real data in class (under NDA).
First Pilot Scope
We start with a short assessment and a first block: for example, a bootcamp for a seed group focused on solving one specific pain point (e.g. automating their reports in Power Query), so the organization sees a working product before scaling up.
⏱️ Duration: 1-4 weeks
🎯 Focus: Early Adopters Team
How we measure value
- • Products finished and deployed by the participants.
- • Process hours saved, as reported by graduates.
- • Post-course surveys on confidence and technology adoption.
Risks & Limitations
- • If management doesn’t let employees dedicate time, the project will fail.
- • We don’t promise to turn someone without basic business logic into a Data Scientist. We teach practical data literacy.
Ready to empower your talent?
Design a Training PathNot sure if this is the right solution?
Use Opportunity RadarThe Madriguera Method™
We don't build technology for the sake of it; we solve real problems through a structured 6-step process. Fast pilots, measurable results.
1. Assessment
2. Roadmap
3. MVP
4. Feedback
5. Delivery
6. 3-mo Impact