University training sustAIn.brussels

Short presentation

Is your SME ready to go Digital in a Sustainable way?

This training course is intended only for SMEs, mid-caps and non-profit organisations!

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  • Programme title
    University training sustAIn.brussels
  • Programme mnemonic
    FC-873
  • Programme organised by
    • Centre de formation continue en Technologies et en Sciences
    • Vrije Universiteit Brussel
    • Centre de formation continue en Technologies et en Sciences
    • Université libre de Bruxelles
  • Title type
    formation continue
  • Field and branch of study
    Sciences and technics/other/Sciences/Engineering sciences
  • Open to returning students
    yes
  • Schedule type
    Daytime
  • Languages of instruction
    english
  • Programme duration
    medium (6 to 15 days), short (2 to 5 days)
  • Campus
    Other campus, FARI - BeCentral
  • Category / Topic
    Economics and business management - Business management/Sciences and technics - Sciences/Sciences and technics - Sciences and technics/Human and social sciences - Information and communication
  • Exam board – additional information
    Team sustain 2.0 :
    • Marie-Mo VAEYENS
    • Yavuz SARIKAYA
    • Mélissa Ranwez
    • Charlotte STIEVENART
To submit

Presentation

Details

General information

Title type

formation continue

Programme duration

medium (6 to 15 days), short (2 to 5 days)

Learning language(s)

english

Schedule type

Daytime

Campus

Other campus, FARI - BeCentral

Category(ies) - Topic(s)

Economics and business management - Business management/Sciences and technics - Sciences/Sciences and technics - Sciences and technics/Human and social sciences - Information and communication

Organising faculty(s) and university(ies) Open to returning students

yes

Customise your own sustAIn.brussels training track ! 
 

Financial aid (grants, training vouchers, etc.)

The sustAIn training tracks are designed to be free of financial contribution from the participant upon the condition of the participant's company to be eligible for some administrational/legal conditions.

* Deminimis-declaration with the sustAIn training tracks service offer: The company declares not exceeding state-support of 300 000 EURO over the last three years, if including the state-aid funded into this program (which is by convention with the Brussels region recognized as per SME at 1687 euro per organized training day, to be multiplied by the number of days you selected). This declaration with the service offer is established at the ULB administration, signed by ULB, after which the company is invited to sign as well.

If you are not eligible for the free training but still interested, you may contact techsci@ulb.be for alternative options.

Formation continue

Contacts

026502240

techsci@ulb.be

https://formationcontinue.ulb.be/fr/sciences-et-techniques

techsci@ulb.be

To schedule a call with a member of our team, please don't hesitate to reach out via email.

Register for :
1. Introduction to data-Driven Decision Making

Teachers

In progress
  • Jacopo DE STEFANI
  • Valentin DIRKEN
  • Yann-Aël LE BORGNE
  • Valentina DALLA GIOVANNA
  • Ilker MAKINE
  • Jules DELCON
  • Guest speakers
  • and many more
  logo techsci

partner universities

Presentation

This program is particularly designed to train members from Small and Medium-sized Enterprises (SME's) in Brussels to facilitate digitalization of these SME's in a sustainable way

Attending

Mondays, Tuesdays and Wednesdays from 12 to 16 PM

Daytime

Format : from March to December 2026
3 days on site - 12 hours
  • Introduction to Data-Driven Decision Making (Jacopo De Stefani)
  • Managing a Data Project (Jacopo De Stefani)
  • Next-generation AI Assistants (Yann-Aël Le Borgne)
  • Building Advanced AI Agent Workflows with LLMs (Yann-Aël Le Borgne)
  • AI Under EU Digital Law: Essential Insights & Legal Opportunities (Valentina Dalla Giovanna)
  • Architecting Digital Success for Your SME (Valentin Dirken)
  • The "Low-Cost RAG" (lker Makine)
  • Sustainability (Jules Delcon)
  • and many more

The project is built on a practical and modular learning approach, tailored to the concrete needs of Brussels-based SMEs.
It combines academic expertise with real-world business cases, translating complex topics such as AI, data, and sustainability into actionable insights.
The pedagogy is action-driven, focusing on tools and methods that can be immediately applied within the company.
Training tracks are flexible and customizable, allowing SME leaders and teams to target their specific challenges.
Learning emphasizes hands-on practice and peer exchange, rather than abstract theory.
The ultimate goal is to strengthen SMEs’ decision-making capacity and innovation potential in their digital and sustainable transition.

Calendar & registration

Prerequisites

SME's from Brussels

Target audience

This training course is intended only for SMEs, mid-caps and non-profit organisations!

Calendar & registration

Customise your own sustAIn.brussels training track ! 

REGISTER for Introduction to data-Driven Decision Making

Additional information

This program is organised in the context of sustAIn.brussels, which has a series of other services to offer.

For more information check out the project's website here Get on track with your company’s digital an sustainable innovation
"During a 30-minute conversation, we'll explore where you are in your digital journey and assess your digital and sustainable training and transformation needs." Link to the registration form : Contact Us | sustAIn.brussels

Programme

Customise your own sustAIn.brussels training track ! 
Tracks oriented towards management:

1. Introduction to Data-Driven Decision Making (Jacopo De Stefani)

*Non technical

Learning outcomes :
By the end of this course, the participants of the course will be able to:

  • Explain the core concepts involved in a Data Science project (i.e. data, data storage, data analysis, predictive modeling).
  • Visualize different data types using industry standard no-code tools
  • Compute descriptive statistics (mean, median, correlation) on tabular datasets
  • Understand the ethical implications and possible causes of bias in a data analysis project.
Expected Deliverables : 

During the course, the participants of the course will develop:

  • Exploratory Data Analysis Summary: An executive summary (-5 points) of initial findings
  • Interactive Insight Dashboard: A public link to a working Low-Code/No-Code dashboard that effectively addresses a business question (e.g., "Which day of the week generates the highest engagement?").
  • Decision-Making Memo: A one-page, non-technical memo written for a manager, detailing the interpreted results of a predictive model and including actionable reccomandations.

2. Managing a Data Project (Jacopo De Stefani)

* More technical
Learning outcomes :

By the end of this course, the participant should be able to:

  • Frame a Data Problem: Clearly define the business objective and success metrics for a data science project, aligning technical efforts with business value.
  • Apply Project Methodologies: Utilize methodologies like CRISP-DM and concepts from Agile/Scrum to plan, organize, and track project tasks effectively.
  • Ensure Governance: Implement simple systems for data governance and documentation, including tracking data sources and transformations.
  • Plan Deployment and Monitoring: Understand the basic concepts of MLOps (Model Operations) necessary for deploying a model and monitoring its performance over time (checking for model drift).
  • Communicate Strategically: Develop and deliver presentations that effectively communicate project results, risks, and ROI to non-technical, executive audiences.
Expected Deliverables : 

Participants will produce:

  • Project Charter Document: A formal document defining the project goals, scope, and initial data requirements
  • Kanban Project Board: A live project board demonstrating task management
  • Data Log: A shared document tracking data source and transformation steps.
  • Executive Project Summary Deck: A short presentation focusing on the Business Value, Model Risks, and Monitoring Plan for the final solution.

3. Next-generation AI Assistants (Yann-Aël Le Borgne)

*Non technical

Learning outcomes :

  • Understand the fundamentals of generative AI and modern AI assistants.
  • Identify practical use cases that increase productivity across sectors.
  • Learn to evaluate AI-generated outputs critically and responsibly.
  • Build simple automation workflows using no-code tools (e.g., n8n).

Expected Deliverables : 
Participants will leave with :

  • A customised AI-generated workflow (via n8n or equivalent) automating at least one organisational task (e.g., monitoring trends, summarising news, generating social posts).
  • A set of best practices for responsible and effective use of AI assistants.

4. Building Advanced AI Agent Workflows with LLMs (Yann-Aël Le Borgne)

*More technical
Learning outcomes :

  • Understand the internal mechanics of LLMs and embeddings at a technical level.
  • Use APIs (OpenAI, Anthropic, open-source LLMs) to integrate AI into workflows.
  • Leverage the HuggingFace ecosystem for model selection, fine-tuning, and deployment.
  • Build data-processing pipelines for emails, reviews, accounting documents, OCR, etc.
  • Create a functional user interface (UI) using Gradio or similar frameworks

Expected Deliverables : 
 

Participants will produce:

  • A full end-to-end workflow that ingests large volumes of text/image/sound, analyses them with LLMs + semantic clustering, and presents insights through a Gradio interface.
  • A reusable codebase(Python + API integrations) that can be adapted to organisational datasets.
  • A set of technical guidelines and best practices for deploying AI tools responsibly and efficiently.