Workshops, mentorship and multi-week programmes built around the tools, data and problems your team works with every day.
A team that can run it without us
The other half of the same problem is what happens after a system ships: if only the vendor understands it, the client is dependent for as long as it runs. Training the team isn't a courtesy add-on — it's what makes the decision actually stick.
How we work
Three steps, always the same. The call comes before the build, and the training comes after — never the other way around.
Train
1:1 mentorship, team workshops, multi-week bootcamps, and self-paced courses on LinkedIn Learning — so the team runs it, not us.
What this looks like in production
The same training we build for one team we have taken to scale: courses on LinkedIn Learning that reach thousands of students who never sit in the same room as us.
LinkedIn Learning courses
Seven active courses on Claude Code, Python and machine learning for energy, data analytics, and AI for physicians — all taught by Jesús López, datons' founder.
Built for yours. Workshops and bootcamps start from your codebase and your team's actual gaps, not a fixed curriculum — the LinkedIn Learning courses are the only self-paced, generic format.
Who teaches the courses?
Jesús López, datons' founder, teaches all seven — the same person who has run the projects behind the advice.
Can we start with just the courses and add consulting later?
Yes, in either order — some teams start with a course to get everyone on the same page, others start with an assessment and bring in training once the direction is set.
Combine modules from the public library and send us your selection for a tailored programme.
Setup & Environment
Claude Code Setup
Install and configure Claude Code for AI-assisted development
3
AI for medical research: from question to finished manuscript Claude Code for Energy
Setup & Environment
Download materials
Clone the course repository with all exercises and resources
1
Setup & Environment
ENTSO-E Setup
Connect to Europe's official energy data source and run your first queries. You'll learn to adapt notebook templates to your own analysis cases — the foundation for all energy work in this course.
4 1
Setup & Environment
Install Git
Install and verify Git on macOS and Windows
2
Setup & Environment
Install Jupyter Lab
Install Python and Jupyter Lab on macOS and Windows
2
Python for Energy — Applied
Setup & Environment
Install Miniconda
Download and configure Miniconda on macOS and Windows
2
Python for Energy — Applied
Setup & Environment
Advanced environment setup
Install scikit-learn, SHAP and ML dependencies
2
Machine Learning for Energy — Advanced
Setup & Environment
Update materials
How to pull the latest updates to your course materials
1
Setup & Environment
Python help menus in VS Code
Use VS Code's built-in help to explore Python functions and modules
1
Setup & Environment
VS Code Setup
Install and configure Visual Studio Code for AI-assisted development
3
AI for medical research: from question to finished manuscript Python for Energy — Applied+1
Python Fundamentals
Data handling with pandas
Manipulate time series of prices, generation and consumption
5 1
Python for Energy — Applied
Python Fundamentals
Introduction to Python
Python basics: data types, variables, control flow, functions
4 1
Python for Energy — Applied
Databases
PostgreSQL database integration
Query and load energy market data directly from Python
3 1
Python for Energy — Applied
Excel & Automation
Excel export and report generation
Generate formatted multi-sheet reports with xlwings
2 1
Python for Energy — Applied
Excel & Automation
Process automation and file handling
Move and organize files automatically, process data reproducibly
2 1
Python for Energy — Applied
Excel & Automation
Integrating exercise
End-to-end exercise combining all modules
1
Python for Energy — Applied
Excel & Automation
Reading and generating XML files
Read and generate XML files for energy market integration
2 1
Python for Energy — Applied
Machine Learning
Introduction to ML for energy
Machine Learning fundamentals applied to energy markets
Export models, automate predictions, integrate with databases
3
Machine Learning for Energy — Advanced
Machine Learning
Model interpretability
Understand what drives predictions with SHAP and feature importance
4
Machine Learning for Energy — Advanced
Machine Learning
Pattern detection & anomalies
Clustering, Isolation Forest and correlation analysis
3 1
Machine Learning for Energy — Advanced
Machine Learning
Random Forest & Gradient Boosting
Build predictive models with scikit-learn
4
Machine Learning for Energy — Advanced
Machine Learning
scikit-learn pipelines
Automate preprocessing, tuning and evaluation
2 1
Machine Learning for Energy — Advanced
Machine Learning
Time series concepts
Temporal features and introduction to ARIMA-type models
3
Machine Learning for Energy — Advanced
AI & Agents
AI agents as programming assistants
Use LLMs as technical copilots for code generation, optimization and validation
4 1
Machine Learning for Energy — Advanced
AI & Agents
AI Energy Analytics
Instructor runs energy queries with the agent, then pauses to read and explain the code behind each step. Students learn what DataFrames are, how queries work, what visualizations do under the hood, and how to spot errors — shifting from vibe coding to code comprehension.
1 7
AI & Agents
AI Energy Dashboard
Instructor builds a dashboard live following a structured workflow: first sketch what charts to show, then define the frontend structure, then implement with the agent, then iterate to polish. Design-first, not prompt-and-pray.
1 4
AI & Agents
Claude Code Fundamentals
Master Claude Code - Anthropic's AI CLI that transforms how you write code. From running scripts to web scraping with MCP.
5
Demos & Use Cases
Use case demos & environment check
Live demos of what you will build and verify your setup works
2 1
Demos & Use Cases
Advanced demos & environment check
Live demos of ML predictions and anomaly detection
2 1
Other
The team application
Each person's dashboard becomes a module of a shared application in the team repository: issues, branches, pull requests with tests in continuous integration, peer review, conflicts and integration.
3 4
AI and data applications for Fortia technical teams
Other
Go deeper: the repository teaches Claude
For those who finish their task: what Claude reads when it opens the shared repository, how to improve AGENTS.md with what you learned, a team command in .claude/skills and shared permissions in .claude/settings.json, all through pull requests.
4
AI and data applications for Fortia technical teams
Other
An animated video of your dashboard
Turn your dashboard's figures and chart into a short animated video, in your company's branding, for a presentation or a message to the team.
1
AI and data applications for Fortia technical teams Python and AI for the electricity sector+1
Other
ChatGPT in the browser
First steps with ChatGPT, the plugins that connect it to other apps (such as Gmail) and Sites to build a website from a conversation.
3 1
Generative AI for IT teams
Other
Usage, limits and settings
How ChatGPT and Codex usage limits work, where to see what you have used, how to make it last and where everything is configured.
2 1
Generative AI for IT teams
Other
Advanced Claude Code practical cases
Beyond the basics: an agent that browses the web for you, and a tour of community-built resources that multiply what you can do without building it from scratch.
2 1
Claude Code for Energy
Other
Artifacts
From an answer with figures to a chart, and from there to a dashboard in an artifact that you share with your team.
3
AI and data applications for Fortia technical teams Python and AI for the electricity sector+1
Other
Skills and plugins
Turn a recurring analysis into a skill, share it with your team, understand why an AI-native company writes what it knows for agents, and distribute your skills in a plugin.
3 1
AI and data applications for Fortia technical teams Python and AI for the electricity sector+1
Other
Connectors
Connect Claude Desktop to Microsoft 365, electricity market data and your company's connectors with your own identity, check them with a couple of charts from each, and ask your first questions about your data in natural language.
2
AI and data applications for Fortia technical teams Python and AI for the electricity sector+1
Other
Context
What the model receives with every message (your connectors' tools, your skills, the project and memory) and how to use it with a project that keeps your business context.
4 1
AI and data applications for Fortia technical teams Python and AI for the electricity sector+1
Other
Email, calendar and Teams
With the Microsoft 365 connector, summarize email threads, review your calendar and draft an email with your dashboard's result, always reviewing it before sending.
1
AI and data applications for Fortia technical teams AI for Fortia's management
Other
Scheduled tasks
Have Claude do a job on its own at the time you choose: first by asking in the conversation, then from the Scheduled screen, field by field.
2
AI and data applications for Fortia technical teams Python and AI for the electricity sector+1
Other
Automate documents with Claude Code
From a messy PDF to structured data in Excel or CSV, without writing a parser: Claude Code reads the document, understands the tables, and exports the result.
1 1
Claude Code for Energy
Other
Claude Code fundamentals
How Claude Code works and what each permission mode controls: your first real conversation with it and how to choose the right mode for each task. Every block pairs a live explanation with your own hands-on case.
2 2
AI for medical research: from question to finished manuscript Claude Code for Energy
Other
Before the course: set up Claude in your browser
Sign in to claude.ai with your work account, connect your company's data and electricity market data. All from the browser, with nothing to install.
2
AI for Fortia's management
Other
Personalize and extend Claude Code
How to take Claude Code beyond an isolated conversation: connect it to your live data via connectors, work on a result live with artifacts, package your own way of working into skills, and share them with your team as a plugin. Every block pairs a live explanation with your own hands-on case.
4 3
AI for medical research: from question to finished manuscript Claude Code for Energy
Other
Claude Code for statistical analysis
Generate and run your dataset's descriptive and statistical analysis with Claude Code, produce the charts that go with it, and interpret the results to plan your manuscript's structure.
1 1
AI for medical research: from question to finished manuscript Claude Code for Energy
Other
Build your agent with Codex
With four messages to Codex, you turn a case from your work into a Python agent that analyses free-text requests with the OpenAI API, with a web app and a local database to use it, and you check it before calling it done.
1 3
Generative AI for IT teams
Other
Data, dashboard and chat on your application
On the application you built with your agent, whatever its case: you generate 10,000 synthetic records with code and check them, build an analysis dashboard and add a chat to ask the data in natural language, always seeing the SQL query.
3
Generative AI for IT teams
Other
Plan before you build
Working with an agent like Codex: plan before implementing, choose the reasoning level and save versions with Git so you can undo.
3 2
Generative AI for IT teams
Other
Codex in VS Code
How an agent works on a folder of files and what its permissions control; you open in VS Code the code of a website built with Sites and create a project from scratch with Codex.
1 2
Generative AI for IT teams
Other
Setting up your environment
What must be ready before the first class (accounts, installs and network) and installing VS Code and Codex in the classroom.
1 1
Generative AI for IT teams
Other
Streamlit and real data: build your own application
Learn Streamlit to turn any Python script into a web application — manage data, visualize large volumes, export reports — and close it by connecting real Spanish electricity market data via the public ESIOS API, with a first simple forecast.
3 3
Claude Code for Energy
Other
Your lakehouse data: from Python to a dashboard
With Claude Code in VS Code and /fabric:lakehouse, create your project from an empty folder, chart a figure of one of your installations in Python, turn it into a SvelteKit dashboard and add a question of your own.
1 3
AI and data applications for Fortia technical teams Python and AI for the electricity sector
Other
Your calculation with Flake data
With /fabric:lakehouse, replace the reading of an exported Excel file with a direct lakehouse query and run the same Python calculation, without touching the calculation or its tests.
1
AI and data applications for Fortia technical teams
Other
Before the course: Prepare your computer
Activate Claude Code in VS Code with your corporate account and ask Claude to prepare the rest: Git, Bun, uv, Azure CLI, the fabric plugin, and Claude Desktop with Microsoft 365.
2
AI and data applications for Fortia technical teams Python and AI for the electricity sector
Other
Your instructor: Jesús López
Who teaches the course, what he does and how he uses AI in his daily work. Shared by every course Jesús López teaches: anything course-specific goes in that course's introduction module.
1
Generative AI for IT teams
Other
Your manuscript's descriptive table
Turn clinical objectives into operational variables, an auditable dataset and the baseline characteristics table — Table 1, with the right statistical tests — ready for the manuscript.
3 3
AI for medical research: from question to finished manuscript
Other
Structuring and preprocessing real-world data
Apply everything you've learned to the data you actually have: load raw exports from different sources, define a clear target structure, and preprocess them into something analysis-ready.
1 1
AI for medical research: from question to finished manuscript
Other
From data to a finished manuscript
Go straight to the parts of the manuscript you actually have to produce: an analysis plan, the figures, the written text and the congress poster.
3 3
AI for medical research: from question to finished manuscript
Other
Survival models and learning curves
Understand two applied medical analyses through real cases, and produce the figures and conclusion statistics that go straight into your results and discussion sections.
3 3
AI for medical research: from question to finished manuscript
Other
Your AI working system
Move from typing into a chat window to a project that runs your analyses, logs what it did and reuses instructions across the whole write-up — no programming background required.
3
Other
The API in real cases: extraction, RAG and frameworks
Two real cases on the Official Bulletin of Castilla y León: batch-extracting the data of 18 announcements into an Excel table, measured against announcements reviewed by hand, and an assistant that answers over those announcements citing the source (RAG). Also, how the model calls your functions and when a framework like LangChain is worth it over the OpenAI SDK.
2 1
Generative AI for IT teams
Other
The agent from the inside: the OpenAI API from Python
What is inside the agent you built with Codex, step by step: the OpenAI API from Python, the instructions, the output schema, the model call and the web app that uses it. And how the same pattern processes hundreds of cases in a script.
2 4
Generative AI for IT teams
Other
Custom assistants
Custom instructions and projects: how to turn a prompt that works into a workspace you reuse and share with your team.
1 1
Generative AI for IT teams
Other
Real IT cases with Codex
Three Codex recipes for everyday IT work: turning an agent into a small management app with its database, writing a read-only admin script, and answering questions about data with SQL and regular expressions. In all of them, checking the result is what matters.
3
Generative AI for IT teams
Other
Responsible use and final project
Agents and automation with judgement, governing AI use in an IT team, and the assessed final project.
2 1
Generative AI for IT teams
Other
Using AI with judgement
Which data may go into AI in the public sector, what the rules require and how to verify what the model says before using it.
1 1
Generative AI for IT teams
Other
Generative AI fundamentals
What a language model is and why it gets things wrong, how model, application, agent, prompt, plugin and skill fit together, which models are available and how each affects quality, speed and usage.
3 1
Generative AI for IT teams
Other
Course introduction
What you will be able to do at the end, how the course works and is assessed, how to use this site and who is in the group.
1 1
Generative AI for IT teams
Other
Open models running locally
What hardware you need, how to run an open-weight model on your own machine, what fine-tuning is and the options to serve one in an organisation: locally, renting a GPU by the hour or on your own infrastructure.
3 1
Generative AI for IT teams
Other
Prompt engineering
What makes a prompt work, how to give the model context and examples, the most common mistakes and how to split a complex task into steps. All in Codex on real IT files: incidents, logs, scripts and documentation.
3 3
Generative AI for IT teams
Other
Day 1 recap
Five quick questions to consolidate day 1: the concept map, models, plugins, Sites, Codex and skills.
1
Generative AI for IT teams
Other
Day 2 recap
Six quick questions to consolidate day 2: planning with /plan and /goal, reasoning levels, Git, measuring a prompt and building a safe agent.
1
Generative AI for IT teams
Other
Day 3 recap
Six quick questions to consolidate day 3: synthetic data and dashboard, structured outputs, the four pieces of the agent, cost at scale and the API key.
1
Generative AI for IT teams
Other
Daily feedback
A two-minute anonymous questionnaire at the end of each course day, to adjust the next day to what the group needs.
4
Other
Your PDF report from the dashboard
Turn your dashboard into a printable weekly report with your company's visual identity and generate the PDF without clicks, with the same server queries.
2
AI and data applications for Fortia technical teams Python and AI for the electricity sector
Other
How the Joltio Data API is organised
Understand why the queries behind your charts look the way they do: which tables exist, what a programme is, how they keep the latest version of each data point, how to explore the catalogue and how to avoid the most common errors.
2 1
Joltio Data: work with electricity market data
Other
Build a dashboard with Streamlit and Joltio data
Turn your queries and charts into an interactive web application with Streamlit: period selector, key metrics, charts, table and data download, with cached queries.
1 2
Joltio Data: work with electricity market data
Other
More examples: market, generation and demand
Practise with real examples: intraday versus day-ahead, cheapest hours, generation mix by technology and actual versus forecast demand, and finish by answering a question of your own.
3
Joltio Data: work with electricity market data
Other
Electricity-market data with Joltio
Query OMIE prices and I90 unit schedules with SQL on the Joltio Data API: first a Python script with the joltio library, then the cross with your installation in the dashboard with @joltioapp/client.
2
Python and AI for the electricity sector
Other
Set up your working environment
Install and check the three tools you will use in the course: VS Code with its extensions, uv to manage Python and Claude Code as an assistant, all with step-by-step instructions.
3
Joltio Data: work with electricity market data
Other
First charts with real electricity market data
Connect a Jupyter notebook in VS Code to the Joltio Data API with your personal key and draw your first charts with real day-ahead market prices, without needing to understand yet how the API is organised.
2
Joltio Data: work with electricity market data
Other
From macro to web
With Claude Code and /excel:migrate, in two steps: the migration plan, which you review and approve, and the implementation in one go up to the web form, with tests that prove it gives the same results as the macro. Then, how it all connects and your own macro.
3 1
AI and data applications for Fortia technical teams
Other
Go deeper: the macro, the port and the workbook inside
For those who want to go further: have Claude explain the macro, fix a quirk test-first, measure macro against Python, review the port with a map and a hidden bug, and how Excel stores formulas and values.
5
AI and data applications for Fortia technical teams
Other
Skills in ChatGPT and Codex
What a skill is, how ChatGPT in the browser and Codex on your computer use it, and how to create your own for a procedure you repeat.
1 1
Generative AI for IT teams
Need custom training?
Combine the modules you need to create a program tailored to your team.