Master of Artificial Intelligence in Business and Industry (Bruges) (60 ECTS) Master of Science
Students with a degree obtained at an institution of the Flemish Community
Direct
On the basis of the following degrees, or similar degrees, obtained at an institution of the Flemish Community:
- Master handelsingenieur (Leuven) (Major: Kwantitatieve methoden + Minor: European Affairs Management, Major: Kwantitatieve methoden + Minor: Industrie, technologie en globalisering, Major: Kwantitatieve methoden + Minor: Marketing management, Major: Kwantitatieve methoden + Minor: Onderwijs, Major: Kwantitatieve methoden + Minor: Op verplaatsing, Major: Kwantitatieve methoden + Minor: Sustainable Management, Major: Kwantitatieve methoden + Minor: Technologie en entrepreneurship, Minor: Accountancy en auditing + Major: Kwantitatieve methoden, Minor: Accountancy en financieel management + Major: Kwantitatieve methoden, Minor: Actuariële en financiële wetenschappen + Major: Kwantitatieve methoden, Minor: Economie + Major: Kwantitatieve methoden, Minor: Informatica voor handelsingenieurs + Major: Kwantitatieve methoden, Minor: International business, strategie en innovatie + Major: Kwantitatieve methoden, Minor: Kwantitatieve marketing + Major: Kwantitatieve methoden, Minor: Personeel en organisatie + Major: Kwantitatieve methoden, Minor: Productie en logistiek + Major: Kwantitatieve methoden, Minor: Risk en Finance + Major: Kwantitatieve methoden, Opleidingsonderdelen KU Leuven: Major: Kwantitatieve methoden)
- Master handelsingenieur in de beleidsinformatica (Leuven)
- Master in de industriële wetenschappen: elektromechanica (Brugge, Geel, Gent, Leuven, Sint-Katelijne-Waver)
- Master in de industriële wetenschappen: elektromechanica (Diepenbeek)
- Master in de industriële wetenschappen: elektronica-ICT (Brugge, Geel, Gent, Leuven, Sint-Katelijne-Waver)
- Master in de industriële wetenschappen: elektronica-ICT (Diepenbeek)
- Master of Business Engineering (Leuven) (Courses KU Leuven: Major: Quantitative Methods for Decision Making, Major: Quantitative Methods for Decision Making + Minor: Accounting and Financial Management, Major: Quantitative Methods for Decision Making + Minor: Actuarial and Financial Engineering, Major: Quantitative Methods for Decision Making + Minor: Business Informatics for Business Engineers, Major: Quantitative Methods for Decision Making + Minor: Economics, Major: Quantitative Methods for Decision Making + Minor: European Affairs Management, Major: Quantitative Methods for Decision Making + Minor: Exchange, Major: Quantitative Methods for Decision Making + Minor: Industry, Technology and Globalization, Major: Quantitative Methods for Decision Making + Minor: International Business, Strategy and Innovation, Major: Quantitative Methods for Decision Making + Minor: Marketing Management, Major: Quantitative Methods for Decision Making + Minor: Personnel and Organisation, Major: Quantitative Methods for Decision Making + Minor: Production and Logistics, Major: Quantitative Methods for Decision Making + Minor: Quantitative Marketing, Major: Quantitative Methods for Decision Making + Minor: Risk and Finance, Major: Quantitative Methods for Decision Making + Minor: Sustainable Management, Major: Quantitative Methods for Decision Making + Minor: Technology and Entrepreneurship)
- Master of Business and Information Systems Engineering (Leuven)
- Master of Electromechanical Engineering Technology (Leuven)
- Master of Electronics and ICT Engineering Technology (Leuven)
MA Engineering Technology: Informatics
All MA degrees in Engineering Science
MA Applied Informatics
After admission procedure
Students with different master’s degrees can submit an application file (via email) that will be evaluated by the permanent programme commission.
Students submit an application file (via email) in which they demonstrate that:
- They have the necessary mathematical background for this programme
- They have already completed an academic four-year master programme (or equivalent)
- They have a good command of the English language, both orally and written (at least level B2, preferably C1)
- They have at least basic programming skills
- They are motivated to successfully complete this programme and willing to spend the required effort
The application will be evaluated on these five criteria by the permanent programme commission (POC) of the programme.
Students with a degree not obtained at an institution of the Flemish Community
Students who did not obtain their previous degree(s) at an institution of the Flemish Community should submit an application via the Admissions Office: https://www.kuleuven.be/english/application/.
You can find a list of core documents, which should be submitted with every application, here: https://www.kuleuven.be/english/application/requesteddocuments.
Diploma requirements
MA Engineering Technology: Electromechanical Engineering TechnologyMA Engineering Technology: Electronics and ICT Engineering Technology
MA Engineering Technology: Informatics
All MA degrees in Engineering Science
MA Applied Informatics
MA Business and Information Systems Engineering
MA Business Engineering option Data Science
Language requirements
Students have a good command of the English language, both orally and written (at least level B2, preferably C1)Additional requirements
Students submit an application file in which they demonstrate that:- They have the necessary mathematical background for this programme
- They have already completed an academic four-year master programme (or equivalent)
- They have at least basic programming skills
- They are motivated to successfully complete this programme and willing to spend the required effort
The application will be evaluated on these five criteria by the permanent programme commission (POC) of the programme.
Students with a degree obtained at an institution of the Flemish Community
Direct
On the basis of the following degrees, or similar degrees, obtained at an institution of the Flemish Community:
- Master handelsingenieur (Leuven) (Major Kwantitatieve methoden, Major Kwantitatieve methoden + Minor Corporate Sustainability, Major Kwantitatieve methoden + Minor European Affairs Management, Major Kwantitatieve methoden + Minor Industrie, technologie en globalisering, Major Kwantitatieve methoden + Minor Onderwijs, Major Kwantitatieve methoden + Minor Op verplaatsing, Major Kwantitatieve methoden + Minor Technologie en entrepreneurship, Minor Accountancy en auditing + Major Kwantitatieve methoden, Minor Accountancy en financieel management + Major Kwantitatieve methoden, Minor Actuariële en financiële wetenschappen + Major Kwantitatieve methoden, Minor Economie + Major Kwantitatieve methoden, Minor Informatica voor handelsingenieurs + Major Kwantitatieve methoden, Minor International business, strategie en innovatie + Major Kwantitatieve methoden, Minor Kwantitatieve marketing + Major Kwantitatieve methoden, Minor Personeel en organisatie + Major Kwantitatieve methoden, Minor Productie en logistiek + Major Kwantitatieve methoden, Minor Risk en Finance + Major Kwantitatieve methoden)
- Master handelsingenieur in de beleidsinformatica (Leuven)
- Master in de industriële wetenschappen: elektromechanica (Brugge, Geel, Gent, Leuven, Sint-Katelijne-Waver)
- Master in de industriële wetenschappen: elektromechanica (Diepenbeek)
- Master in de industriële wetenschappen: elektronica-ICT (Brugge, Geel, Gent, Leuven, Sint-Katelijne-Waver)
- Master in de industriële wetenschappen: elektronica-ICT (Diepenbeek)
- Master of Business Engineering (Leuven) (Major Quantitative Methods for Decision Making + Minor Accounting and Financial Management, Major Quantitative Methods for Decision Making + Minor Actuarial and Financial Engineering, Major Quantitative Methods for Decision Making + Minor Business Informatics for Business Engineers, Major Quantitative Methods for Decision Making + Minor Corporate Sustainability, Major Quantitative Methods for Decision Making + Minor Economics, Major Quantitative Methods for Decision Making + Minor European Affairs Management, Major Quantitative Methods for Decision Making + Minor Exchange, Major Quantitative Methods for Decision Making + Minor Industry, Technology and Globalization, Major Quantitative Methods for Decision Making + Minor International Business, Strategy and Innovation, Major Quantitative Methods for Decision Making + Minor Production and Logistics, Major Quantitative Methods for Decision Making + Minor Quantitatieve Marketing, Major Quantitative Methods for Decision Making + Minor Risk and Finance, Major Quantitative Methods for Decision Making + Minor Technology and Entrepreneurship, Major: Quantitative Methods for Decision Making)
- Master of Business and Information Systems Engineering (Leuven)
- Master of Electromechanical Engineering Technology (Leuven)
- Master of Electronics and ICT Engineering Technology (Leuven)
MA Engineering Technology: Informatics
All MA degrees in Engineering Science
MA Applied Informatics
After admission procedure
Students with different master’s degrees can submit an application file (via email) that will be evaluated by the permanent programme commission.
Students submit an application file (via email) in which they demonstrate that:
- They have the necessary mathematical background for this programme
- They have already completed an academic four-year master programme (or equivalent)
- They have a good command of the English language, both orally and written (at least level B2, preferably C1)
- They have at least basic programming skills
- They are motivated to successfully complete this programme and willing to spend the required effort
The application will be evaluated on these five criteria by the permanent programme commission (POC) of the programme.
Students with a degree not obtained at an institution of the Flemish Community
Students who did not obtain their previous degree(s) at an institution of the Flemish Community should submit an application via the Admissions Office: https://www.kuleuven.be/english/application/.
You can find a list of core documents, which should be submitted with every application, here: https://www.kuleuven.be/english/application/requesteddocuments.
Diploma requirements
MA Engineering Technology: Electromechanical Engineering TechnologyMA Engineering Technology: Electronics and ICT Engineering Technology
MA Engineering Technology: Informatics
All MA degrees in Engineering Science
MA Applied Informatics
MA Business and Information Systems Engineering
MA Business Engineering option Data Science
Language requirements
Students have a good command of the English language, both orally and written (at least level B2, preferably C1)Additional requirements
Students submit an application file in which they demonstrate that:- They have the necessary mathematical background for this programme
- They have already completed an academic four-year master programme (or equivalent)
- They have at least basic programming skills
- They are motivated to successfully complete this programme and willing to spend the required effort
The application will be evaluated on these five criteria by the permanent programme commission (POC) of the programme.
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Students take all compulsory courses and complete their programme up to at least 60 credits.
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AI and Industry
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Compulsory Course
This course is compulsory.
6 ECTS Computer Vision and Natural Language Processing H0Q35A staff staff
- P.Vandewalle (coordinator)
- T.Goedemé
- K.Laenen
- P.Delobelle (substitute)
- P.Vandewalle
Computer Vision (2 ECTS) H0Q35a staff Computer Vision and Natural Language Processing: Project (2 ECTS) H0Q36a staff staff
- T.Goedemé
- K.Laenen
- P.Delobelle (substitute)
- P.Vandewalle
Natural Language Processing (2 ECTS) H0Q37a staff- K.Laenen
- P.Delobelle (substitute)
staff
- K.Laenen
- P.Delobelle (substitute)
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Applied AI: Academic Perspectives
Students take one course.
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Applied AI: Industrial Perspectives
Students take one course.
4 ECTS Applied AI: Industrial Perspectives (Two Modules) B30775 staff staff
- J.Vennekens (coordinator)
- N.
- J.Vennekens (cooperator)
Applied AI: Industrial Perspectives (Two Modules) (4 ECTS) B5517V staff- N.
- J.Vennekens (cooperator)
staff
- N.
- J.Vennekens (cooperator)
6 ECTS Applied AI: Industrial Perspectives (Three Modules) B30776 staff staff
- J.Vennekens (coordinator)
- N.
- J.Vennekens (cooperator)
Applied AI: Industrial Perspectives (Two Modules) (4 ECTS) B5517V staff- N.
- J.Vennekens (cooperator)
staff
- N.
- J.Vennekens (cooperator)
Applied AI: Industrial Perspectives (Additional Module) (2 ECTS) B5517W staff- N.
- J.Vennekens (cooperator)
staff
- N.
- J.Vennekens (cooperator)
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Elective courses
4 ECTS Embodied Autonomous Systems B3076U staff staff
- E.Demeester (coordinator)
- H.Bruyninckx
- E.Demeester
- M.De Ryck (cooperator)
Embodied Autonomous Systems: Lecture (2.5 ECTS) B5517G staff staff
- H.Bruyninckx
- E.Demeester
- M.De Ryck (cooperator)
Embodied Autonomous Systems: Experience (1.5 ECTS) B5517H staff staff
- H.Bruyninckx
- E.Demeester
- M.De Ryck (cooperator)
4 ECTS AI in Embedded Systems B3076T staff staff
- H.Hallez (coordinator)
- P.Karsmakers
- M.Verhelst
- K.Wang (cooperator)
AI in Embedded Systems (4 ECTS) B5517F staff staff
- H.Hallez
- P.Karsmakers
- M.Verhelst
- K.Wang (cooperator)
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AI and Business
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Compulsory course
This course is compulsory.
6 ECTS Business Analytics H0Q44A staff- J.De Weerdt (coordinator)
- N.
staff
- J.De Weerdt (coordinator)
- N.
Business Analytics (6 ECTS) H0Q44a staff- N.
staff
- N.
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Elective course
4 ECTS Realization of AI B30778 staff- S.vanden Broucke (coordinator)
staff
- S.vanden Broucke (coordinator)
Realization of AI: Lecture (1 ECTS) B5517Y staff staff
Realization of AI: Project (3 ECTS) B5517Z staff staff
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AI Foundations
All courses are compulsory.
5 ECTS Fundamentals of Artificial Intelligence H0Q38A staff staff
Fundamentals of Artificial Intelligence: Lecture (4 ECTS) H0Q38a staff staff
Fundamentals of Artificial Intelligence: Exercises (1 ECTS) H0Q39a staff staff
4 ECTS Artificial Neural Networks and Deep Learning H0Q42A staff staff
Artificial Neural Networks and Deep Learning: Lecture (3 ECTS) H0Q42a staff staff
Artificial Neural Networks and Deep Learning: Exercises (1 ECTS) H0Q43a staff staff
4 ECTS Machine Learning and Inductive Inference H0Q40A staff- N.
- C.Vens (substitute)
- A.Gharahighehi (substitute)
- F.Nakano (substitute)
- C.Vens (substitute)
- A.Gharahighehi (substitute)
- F.Nakano (substitute)
staff
- N.
- C.Vens (substitute)
- A.Gharahighehi (substitute)
- F.Nakano (substitute)
- C.Vens (substitute)
- A.Gharahighehi (substitute)
- F.Nakano (substitute)
Machine Learning and Inductive Inference: Lecture (3 ECTS) H0Q40a staff staff
- N.
- C.Vens (substitute)
- A.Gharahighehi (substitute)
- F.Nakano (substitute)
Machine Learning and Inductive Inference: Exercises (1 ECTS) H0Q41a staff staff
- N.
- C.Vens (substitute)
- A.Gharahighehi (substitute)
- F.Nakano (substitute)
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AI and Society
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Compulsory Course
This course is compulsary
6 ECTS AI and Society: Core Concepts B3078E staff- E.Terryn (coordinator)
- J.De Bruyne
- B.Reynvoet
- W.Schaeken
- P.Valcke
- T.Folens (cooperator)
- C.Koolen (cooperator)
staff
- E.Terryn (coordinator)
- J.De Bruyne
- B.Reynvoet
- W.Schaeken
- P.Valcke
- T.Folens (cooperator)
- C.Koolen (cooperator)
AI and Society: Core Concepts (6 ECTS) B551A7 staff staff
- J.De Bruyne
- B.Reynvoet
- W.Schaeken
- P.Valcke
- T.Folens (cooperator)
- C.Koolen (cooperator)
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Elective Course
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Master's Thesis
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