3 ECTS credits
75 h study time

Offer 1 with catalog number 8024167HNR for all students in the 1st semester at a (H) Postgraduate - advanced level.

Semester
1st semester
Enrollment based on exam contract
Impossible
Grading method
Grading (scale from 0 to 20)
Can retake in second session
Yes
Enrollment Requirements
Students must have followed 'Introduction to AI' and 'Technology and data', before they can enroll for ‘Case studies in responsible innovation with AI'.
Taught in
English
Faculty
Faculty of Sciences and Bioengineering Sciences
Department
Computer Science
Educational team
Johan Loeckx (course titular)
External teachers
Julien Gossé
Activities and contact hours
24 contact hours Seminar, Exercises or Practicals
Course Content

The student is obliged to write a case study, either within their own company (lifelong learners) or with an external partner (fresh graduates). The goal is for students to integrate all that they have learned 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. 

 
Additional info

NA

 
Learning Outcomes

General Competences

  1. The student shows and integrates his/her learnings from the other modules. 
  2. The student develops a critical attitude towards AI and its applications. 
  3. Explore concrete AI opportunities within their organization and their strategic fit with the organization. The student can make the case of the unique value AI will bring, why AI is the right approach. 
  4. Determine the maturity of their organization and assess its strengths and weaknesses for example in terms of data, technology, skills, business aspects, ethical & legal standards or processes.    
  5. Build a strategic roadmap to implement a concrete AI use case in a     responsible way within their organization 
  6. The student can communicate her/his findings to laymen in an engaging, scientifically sound and accurate manner. 
 

Grading

The final grade is composed based on the following categories:
Other determines 100% of the final mark.

Within the Other category, the following assignments need to be completed:

  • Written assignment with a relative weight of 1 which comprises 100% of the final mark.

Additional info regarding evaluation

Written assignment 

 
Allowed unsatisfactory mark
The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context

This offer is part of the following study plans:
Postgraduate Certificate AI for the Common Good: Default track