Default track
Modules
ECTS credits
Total number of ECTS
20
Details
The programme consists of six modules. For each of the lectures/workshops, the students are expected to spend an equal amount of studying at home.
Module 1: Introduction to AI (4 days - compulsory)
Content lead: Johan Loeckx (VUB)
Gives a basic introduction to the concepts and principles of AI. It explains what AI is, why it is an important evolution, how it works conceptually, what the limits are, and potential. It is mainly aimed to remove common misconceptions, create a common ground and language between the participants and empower them with a framework of understanding for future learnings.
Module 2: Technology & data (3 days - compulsory)
Content lead: Hugues Bersini (ULB)
Examines the technical and data aspects of AI: how does it work? What data should I collect? How to organise a proper data governance? What is the relation between software and hardware in AI? What is the impact on my technology stack? Who are the (cloud) service providers and what are mature Open-Source solutions?
Module 3: Governance & organization (4 days)
Content lead: Gloria Gonzalez Fuster (VUB)
Looks at the impact on implementation and processes: what organisational structures to create to guarantee a trustworthy implementation of AI? How to monitor and evaluate AI (on the governance level)? How to increase the privacy and security characteristics of solutions? What are potential threats? What are the regulations, frameworks and standards?
Module 4: People & Culture (3 days)
Content lead: An Jacobs (VUB)
Zooms in on all the aspects related to people : how to create top performing teams? How to hire? What will the impact be on my staff? What training programmes should I organise? Whom should I involve in AI -related projects? What is the impact on society, on our values, on our thinking?
Module 5: Economics & Business of AI (3 days)
Only available after following module 1 to 4.
Content lead: Nicolas Van Zeebroeck (ULB)
Discusses the impact on the economy, on business models and pricing, and details how calculations on Return-on-Investment can be made. Also, more insights are given into the AI market
Module 6: Case study (3 days - compulsory)
Content lead: Julien Gossé (ULB)
Each student is obliged to write a case study, either within their own company (lifelong learners) or with an external partner (fresh graduates). The learning goal is for students to integrate all what they have learnt and look at a holistic, interdisciplinary way at AI innovation.
The students are asked to identify the opportunities of AI within their institution and create a roadmap that considers the maturity of the organisation, and assesses the potential impact on ethics, legal, technical and governance structures (processes), business model, competitive position, people & training, data management, safety & security. It helps graduates orient. It allows employees to explore potential opportunities, determine the maturity of their organisation, and assess its strengths & weaknesses.