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
    • Université libre de Bruxelles
  • Title type
    formation continue
  • Field and branch of study
    Sciences and technics/other
  • 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
    Solbosch/Uccle
  • 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

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

Solbosch/Uccle

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 ! 
 

Registration Sustainable Digitalization & IT
Registration Datascience 
Registration Artificial intelligence
Registration Machine Learning
Registration Chat gpt next generation assistants
Registration Applications of ai in engineering
Registration Cybersecurity

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

+32 (0)2 650 67 75


techsci@ulb.be

 

Teachers

  • Arjen VAN DE WALLE
  • Bernardo INNOCENTI
  • Dimitris SACHARIDIS
  • Giovanni BRIGANTI
  • Jacopo DE STEFANI
  • Jan Tobias MUEHLBERG
  • Jean CARDINAL
  • Johan LOECKX
  • Olivier CAELEN
  • Olivier DEBEIR
  • Valentin DIRKEN
  • Yann-Aël LE BORGNE


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.

Customise your personalised training track à la carte from 7 offered topics in just two steps:

SUSTAINABLE DIGITALIZATION & IT

  • Strategizing for the Sustainable Transformation of (your) organization
  • Implementing digital technologies sustainably and responsibly

INTRODUCTION TO DATA SCIENCE

From Raw Data to Actionable Insights

ARTIFICIAL INTELLIGENCE

Learn the impact AI has on society !

DESIGNING CYBERSECURITY

Assess your data protection and design the security architecture of your company

MACHINE LEARNING

Demystifies machine learning algorithms tools & gets you to apply them with Python

ChatGPT & Next-generation assistants

Identify the strengths and limits of next generation chatbots for your business

APPLICATIONS OF AI IN ENGINEERING

Join this road show of AI applications to stimulate your computational creativity

Daytime

 
  • Introduction to Data Science*
    • Monday 10 February 2025
    • Wednesday 12 February 2025
    • Friday 17 February 2025
  • Artificial intelligence*
    • Monday 17 February 2025
    • Wednesday 19 February 2025
    • Friday 21 February 2025
  • Machine learning*
    • Monday 10 March 2025 
    • Wednesday 12 March 2025
    • Friday 14 March 2025
  • ChatGPT & Next-generation assistants*
    • Wednesday 2 April 2025
    • Thursday 3 April 2025
    • Friday 4 April 2025
  • Applications of ai in engineering*
    • Tuesday 22 April 2025
    • Thursday 24 April 2025
    • Friday 25 April 2025
  • Designing cybersecurity*
    • Wednesday 3 June 2025
    • Thursday 5 June 2025
    • Friday 6 June 2025
  • Sustainable digitalization & IT*
    • Monday 16 June 2025
    • Wednesday 18 June 2025
    • Friday 20 June 2025

Calendar & registration

Target audience

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

Calendar & registration

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:

Sustainable digitalization & IT 
 

Sustainable digitalization

Strategizing for the Sustainable Transformation of (your) organization

1.    Description
The aim of this course is to introduce participants to the complex relationships between digital technologies and sustainability, considering the environmental, societal and economic pillars. Besides demystifying such relationships, the objective is also to teach participants how this translates practically in organizations’ strategies and operations. To do so, the teachers will rely on both theoretical and practical sessions, where guest lecturers will provide testimonials on how they dealt with such issues and what were the enablers and obstacles in such transformation. Regular and interactive exercises will also be included in the training to allow for participants to immediately reflect on the issues and be able to apply theoretical and practical concepts to their reality. Finally, this course will end up with a cocreation workshop aiming at developing a strategic framework by and for SMEs to navigate such dual transformations. 

2.    Course content & learning outcomes:
Course content
•    Introduction to the concepts of digitalization/digital transformation & sustainability/sustainable development
•    Introduction to the complex relationships between digital technologies and sustainability
•    Strategy development integrating digital transformation and sustainability
•    Organizational, operational and communicational practices
•    Practical testimonials

Learning outcomes:
•    Improve knowledge on digital & sustainability issues at large
•    Understand practical, business implications of such high-level issues 
•    Strategically apply such knowledge to own realities
•    Gain insights on best practices from the field

3.    Teachers : 
  • Arjen van de Walle

Sustainable IT

Implementing digital technologies sustainably and responsibly

1.    Description
The digital transformation of companies goes hand in hand with an aspiration to become more sustainable. As both transformations may change the heart of the business model, making digitalization and sustainability aspirations align can form a key challenge. This course aims to introduce professionals within the business domain to a nuanced, technology-oriented and pragmatic view of the sustainable implementation of digital technologies. The course will provide expert perspectives on cybersecurity and responsible IT practices, and participants will gain an in-depth understanding of the intricate interplay between digital technologies, and environmental and social sustainability in a corporate context. Here, you will gain insight into quantitative metrics essential for viewing sustainability but also show the alignment with broader organizational objectives, both in terms of digital transformation and sustainability (reporting) goals. Participants can expect an interactive course format, integrating online modules with a live workshop.

2.    Course content & learning outcomes:
Course content
•    Introduction to the interlinkage between digitalization and sustainability
•    Linking sustainable IT with broader corporate sustainability and reporting
•    Measuring is knowing: what tools can you use to measure the sustainability impacts of IT
•    Use cases and business-oriented applications of concepts

Learning outcomes:
•    A pragmatic, technology-oriented view on sustainable digitalization in corporate environments
•    Gain an intuition for linking digital technologies with their (often invisible) sustainability impacts
•    Gain knowledge of available tools to measure and report impacts
•    Gain insights on best practices from the field

3.    Teachers : 
  • Arjen van de Walle
  • Yann-Aël LE BORGNE
  • Dimitris Sacharidis
Registration Sustainable Digitalization & IT

Introduction to Data Science

From Raw Data to Actionable Insights

1.    Description
Dive into the world of data-driven decision-making with our comprehensive Data Science course. Designed for professionals from diverse backgrounds this course equips you with essential skills to harness the power of data for insightful analysis and predictive modeling. 
In the first part of the course, we will provide solid theoretical bases, introducing core concepts in data science such as data types, data formats, data quality issues and predictive modeling. In order to facilitate application in practical settings, these concepts will be directly related to existing use cases under the supervision of the course lecturers. For the second part of the course, we will employ industry standard Python packages (e.g. pandas, numpy, scikit-learn), to develop a prototype of a data analysis pipeline. Participants are assumed to already have a working knowledge of programming (ideally Python), but additional self-learning resources will be provided if needed. 

2.    Course content & learning outcomes:
Course content
●    Introduction to Data Science and Data Analytics
●    The four flavors of Data Analytics: Descriptive, Diagnostic, Predictive, Prescriptive
●    Implementing a data analysis pipeline with Python
●    Data Science in Practice: Do’s, Dont’s and Ethical considerations

Learning outcomes:
By the end of this course you should be able to:
●    Explain the core concepts involved in a Data Science project (i.e data types, data storage, data analysis, predictive modeling);
●    Examine an existing situation to identify what suitable Data Science methodologies and analysis are applicable
●    Develop a prototype of a data analysis pipeline using Python and its data science toolkit (pandas, seaborn, sci-kit learn, …)

3.    Teachers : 
  • Jacopo DE STEFAN
  • Jean CARDINAL
  • Yann-Aël LE BORGNE
  Registration Datascience


 

Artificial intelligence

Explore how custom-made AI can be key to your sustainable digitalization

1.    Description
This course delves into the principles of AI and the impact it hason society, using practicalfields (eg: healthcare, biomechanics) and novelties as examples. From AI ideation to AIapplications, you will gain significant insights on the impacts and opportunities AI will have onyour business and on society through its societal dimension.

2.    Course content & learning outcomes:
Course content
  • Introduction: AI: what is it and what it can do?
  • AI applications
  • Legal and ethical aspects of AI
  • Sociological aspects of AI
Learning outcomes
  • Have an overview of the impact AI has insociety.
  • Discover the application of AI with specific topics, such as health, biomechanics, law, ethics and sociology
3.    Teachers : 
  • Giovanni BRIGANTI
  • Bernardo INNOCENTI
 Registration Artificial intelligence


 

Tracks oriented more technically:

 

Machine learning

Demystifies machine learning algorithms tools & gets you to apply them with Python

1.    Description
The aim of this course is to introduce the basic concepts of machine learning. We will have botha theoretical part with slides and a practical part where we will use the Python programminglanguage for the exercises. In the theoretical part, we will introduce concepts such assupervised, unsupervised and reinforcement learning. A few examples of classic algorithms willbe presented, such as tree-based models, naive Bayesian classification and neural networks.Without seeking to formalise too much, the theoretical aspects of machine learning will bepresented both intuitively and using a mathematical formalism. For the programming part, thebasic Python packages used in machine learning will be presented, but participants will beassumed to already have a good command of programming (ideally Python). By the end of thecourse, the aim is to have contributed to demystifying the tools used by data scientists and, inthe advanced track, to have manipulated simple models on real data.

2.    Course content & learning outcomes:
Course content
  • Introduction to Machine Learning from Scratch
  • Simple machine learning models
  • The basics of deep learning
  • Machine learning with Python
Learning outcomes:
  • Improve your knowledge and use of Python;
  • Gain understanding of models and tools used by data scientists;
  • Acquire a solid foundation in machine learning to pursue studies in the field ;
  • Put your theoretical knowledge in programming into practice
  • Gain confidence to apply and manipulate simple p
  • rogramming models on real data

3.    Teachers : 
  • Olivier CAELEN
  • Yann-Aël LE BORGNE
  • Jacopo DE STEFANI
Registration Machine learning



ChatGPT & Next-generation assistants

Identify the strengths and limits of next generation chatbots for your business

1.    Description
The coursewill aim at explaining the nuts and bolts of the new generation of chatbots such asChatGPT, what they can be used for, and what are their limits. We will start with an overviewof reference chatbots (both closed and open source, ChatGPT and Mistral for example),common use cases (writing, summarizing, brainstorming, ...), and some of the main limits ofthese tools (bias, hallucinations, ...). The course will then dive gradually into more advanceduse cases, addressing along the way more subtle issues, bothethical and technical. Examplesof ethical issues that we will address cover data privacy, intellectual property, and the digitaldivide. On the technical side, we will show how chatbots can be programmed and trained, usingeither APIs for closed-source solution, or libraries such as HuggingFace for open-sourcemodels. By the end of the course, the goal is that participants can make their informed decisionson the capabilities of this new type of software, and when and for what they may appropriatelyuse them.

2.    Course content & learning outcomes:
Course content
  • Introduction to large language models (LLMs) such as ChatGPT
  • Experiment with different use cases
  • Discuss about limitations, both technical and ethical
  • Program LLMs, both closed and open-source models (workshop day-technical profile)
  • Design a Chatbot Web application (workshop day-technical profile)

Learning outcomes:
  • Demonstrate an understanding of large language models' technology within the field of machine learning
  • Identify the primary use cases for LLMs and formulate effective prompts
  • Recognize and explain the technical limitations and ethical issues associated with LLMs
  • Use and program with LLMs in Python
  • Apply methods for data augmentation and fine-tuning
3.    Teachers : 
  • Yann-Aël LE BORGNE
  • Olivier CAELEN
  • Jacopo DE STEFANI
 Registration ChatGPT & Next-generation assistants


 

Applications of ai in engineering

Join this road show of AI applications to stimulate your computational creativity

1.    Description
The aim of this course is to introduce executives, project and innovation managers as well as engineers to AI.On the one hand, it will become clear that engineering is a significant part of building AI systems. Likewise existingengineering approaches (like signal processing) have profoundly influenced AI.The main focus, however, is to introduce employees from engineering disciplines, to the broad range of AI techniques(both symbolic techniques as subsymbolic) that were developed over the last 70+years.The course will consist mainly of testimonials from industry professionals that have applied AI or developed noveltechniques within their domain.Also, we will make things more tangible by organising a low-entry hands-on codingworkshop.

2.    Course content & learning outcomes:
Course content
  • 1h Introduction to the intersection of engineering & AI in different disciplines, including electronics, robotics and food design.
  • 1h Overview of common techniques in AI and how they can contribute to engineering;
  • 1h Introduction to engineering practices in AI (like MLOps)–guest speakers
  • 6h Testimonials of practitioners about projects that use AI to improve or complement their engineering (guest speakers);
  • 3h Gain hands-on-experience in a technical workshop.

Learning outcomes:
  • Map how AI can support & complement engineering;
  • Understand how data and knowledge can complement each other;
  • Understand problems and solution related to putting AI in production;
  • Gain knowledge about potential techniques that can be applied;
  • Develop a critical and creative mindset towards data-driven approaches;
  • Understand the limitations of AI techniques.
3.    Teachers : 
  • Olivier DEBEIR
 Registration Applications of ai in engineering




Designing cybersecurity

Assess your data protection and design the security architecture of your company

More information coming soon! 

Registration Cybersecurity