Master of Artificial Intelligence (Leuven) (60 ECTS) Master of Science
Students with a degree obtained at an institution of the Flemish Community
After admission procedure
On the basis of the following degrees, or similar degrees, obtained at an institution of the Flemish Community:
- Master of Engineering: Computer Science (Leuven)
Students with a degree obtained at an institution of the Flemish Community need permission of the programme director to start the programme. More information is to be found here: https://wms.cs.kuleuven.be/cs/studeren/master- artificial-intelligence/application
Additional information
Upon admission, students are recommended to select the option within AI that corresponds to their background:
- the ECS option is only recommended for students with a degree in Science, in Engineering or Applied Economics (majoring in Informatics). Students should have thorough knowledge of at least one programming language, should master an object oriented programming and have sufficient background in Mathematics.
- the SLT option is open to students with a degree in Human Sciences (Economics, Psychology, Philosophy, Arts or Medicine), in addition to all above-mentioned degrees. Students should be familiar with at least one programming language.
- the BDA option is only recommended for students with a degree in Computer Science or Informatics. Several of our students combine their study in AI with a full-time job. Special provisions are made on the basis of the individual courses to make this possible.
Special provisions are made for students who enter the ECS-option without sufficient prior familiarity with Object Oriented Programming. These students are required to select the course Basic Programming as one of their optional courses.
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
Master of Science (in Engineering) in Computer Science, Master of Science (in Engineering) in Informatics, Master of Science (in Engineering) in Information and Communication Technology, Master of Arts (specialisation in Linguistics).We require at least a 4-year university (or equivalent) degree with good study results and experience with computing.
Language requirements
Formal language requirements of the Faculty of Engineering ScienceAdditional requirements
In order to be considered for admission, applicants are required to submit a GRE test. Students who obtained a Bachelor’s or a Master’s degree in one of the EEA countries, the UK, or Switzerland are exempted from providing GRE scores.Please contact ETS to make sure that your score is made available to KU Leuven in the online ETS verification tool. The institutional code of KU Leuven is 0749.
Additional information
Upon admission, students are recommended to select the option within AI that corresponds to their background:
- the ECS option is only recommended for students with a degree in Science, in Engineering or Applied Economics (majoring in Informatics). Students should have thorough knowledge of at least one programming language, should master an object oriented programming and have sufficient background in Mathematics.
- the SLT option is open to students with a degree in Human Sciences (Economics, Psychology, Philosophy, Arts or Medicine, in addition to all above-mentioned degrees. Students should be familiar with at least one programming language.
- the BDA option is only recommended for students with a degree in Computer Science or Informatics.
Several of our students combine their study in AI with a full-time job. Special provisions are made on the basis of the individual courses to make this possible.
Special provisions are made for students who enter the ECS-option without sufficient prior familiarity with Object Oriented Programming. These students are required to select the course Basic Programming as one of their optional courses.
Students with a degree obtained at an institution of the Flemish Community
After admission procedure
On the basis of the following degrees, or similar degrees, obtained at an institution of the Flemish Community:
- Master of Engineering: Computer Science (Leuven)
Students with a degree obtained at an institution of the Flemish Community need permission of the programme director to start the programme. More information is to be found here: https://wms.cs.kuleuven.be/cs/studeren/master- artificial-intelligence/application
Additional information
Upon admission, students are recommended to select the option within AI that corresponds to their background:
- the ECS option is only recommended for students with a degree in Science, in Engineering or Applied Economics (majoring in Informatics). Students should have thorough knowledge of at least one programming language, should master an object oriented programming and have sufficient background in Mathematics.
- the SLT option is open to students with a degree in Human Sciences (Economics, Psychology, Philosophy, Arts or Medicine), in addition to all above-mentioned degrees. Students should be familiar with at least one programming language.
- the BDA option is only recommended for students with a degree in Computer Science or Informatics. Several of our students combine their study in AI with a full-time job. Special provisions are made on the basis of the individual courses to make this possible.
Special provisions are made for students who enter the ECS-option without sufficient prior familiarity with Object Oriented Programming. These students are required to select the course Basic Programming as one of their optional courses.
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
Master of Science (in Engineering) in Computer Science, Master of Science (in Engineering) in Informatics, Master of Science (in Engineering) in Information and Communication Technology, Master of Arts (specialisation in Linguistics).We require at least a 4-year university (or equivalent) degree with good study results and experience with computing.
Language requirements
Formal language requirements of the Faculty of Engineering ScienceAdditional requirements
In order to be considered for admission, applicants are required to submit a GRE test. Students who obtained a Bachelor’s or a Master’s degree in one of the EEA countries, the UK, or Switzerland are exempted from providing GRE scores.Please contact ETS to make sure that your score is made available to KU Leuven in the online ETS verification tool. The institutional code of KU Leuven is 0749.
Additional information
Upon admission, students are recommended to select the option within AI that corresponds to their background:
- the ECS option is only recommended for students with a degree in Science, in Engineering or Applied Economics (majoring in Informatics). Students should have thorough knowledge of at least one programming language, should master an object oriented programming and have sufficient background in Mathematics.
- the SLT option is open to students with a degree in Human Sciences (Economics, Psychology, Philosophy, Arts or Medicine, in addition to all above-mentioned degrees. Students should be familiar with at least one programming language.
- the BDA option is only recommended for students with a degree in Computer Science or Informatics.
Several of our students combine their study in AI with a full-time job. Special provisions are made on the basis of the individual courses to make this possible.
Special provisions are made for students who enter the ECS-option without sufficient prior familiarity with Object Oriented Programming. These students are required to select the course Basic Programming as one of their optional courses.
-
This group comprises the three specialisations within the Master of Artificial Intelligence. Students have to select one of the three specialisations:
1. Engineering and Computer Science (ECS),
2. Speech and Language Technology (SLT),
3. Big Data Analytics (BDA).-
Specialisation: Engineering and Computer Science (ECS)
Students follow all subgroups of the option, according to the rules defined in these subgroups.
-
ECS Introductory Components
Students follow all courses in the ECS Compulsory Introductory Components subgroup and select 4 credits from the ECS Elective Introductory Components subgroup.
-
ECS Compulsory Introductory Components
Students follow all courses within this group.
5 ECTS Fundamentals of Artificial Intelligence H02A0A staff staff
Fundamentals of Artificial Intelligence: Lecture (3 ECTS) H02A0a staff staff
Fundamentals of Artificial Intelligence: Exercises (1 ECTS) H02K1a staff staff
Fundamentals of Artificial Intelligence: Project (1 ECTS) H0O43a staff staff
-
ECS Elective Introductory Components
Students select 4 credits from the courses offered in this group.
4 ECTS Cognitive Science H02B2A staff- W.Schaeken
- H.Stuyck (substitute)
staff
- W.Schaeken
- H.Stuyck (substitute)
Cognitive Science: Lecture (3.5 ECTS) H02B2a staff- W.Schaeken
- H.Stuyck (substitute)
staff
- W.Schaeken
- H.Stuyck (substitute)
Cognitive Science: Exercises (0.5 ECTS) H00G1a staff- W.Schaeken
- H.Stuyck (substitute)
staff
- W.Schaeken
- H.Stuyck (substitute)
4 ECTS Privacy and Big Data H00Y2A staff staff
- R.Gálvez Vizcaíno
- N.
- R.Gálvez Vizcaíno (substitute)
Privacy and Big Data: Lecture (3 ECTS) H00Y2a staff- N.
- R.Gálvez Vizcaíno (substitute)
staff
- N.
- R.Gálvez Vizcaíno (substitute)
Privacy and Big Data: Practical Sessions (1 ECTS) H00Y3a staff staff
4 ECTS Philosophy of Mind and Artificial Intelligence H02D5A staff staff
Philosophy of Mind and Artificial Intelligence (4 ECTS) H02D5a staff staff
4 ECTS AI Ethics & Regulation H0P05A staff- N.
- A.Kuczerawy (substitute)
staff
- N.
- A.Kuczerawy (substitute)
AI Ethics & Regulation: Lecture (4 ECTS) H0P05a staff- N.
- A.Kuczerawy (substitute)
staff
- N.
- A.Kuczerawy (substitute)
-
-
ECS Programming Component
All students have to take the course offered in this group.
-
ECS Advanced Mandatory Components
Students have to take all courses in this subgroup.
4 ECTS Machine Learning and Inductive Inference H02C1A staff staff
Machine Learning and Inductive Inference: Lecture (3 ECTS) H02C1a staff staff
Machine Learning and Inductive Inference: Exercises (1 ECTS) H00G6a staff staff
4 ECTS Uncertainty in Artificial Intelligence H02D2A staff staff
- L.De Raedt (coordinator)
- T.De Laet
- L.De Raedt
Uncertainty in Artificial Intelligence: Lecture (3 ECTS) H02D2a staff staff
Uncertainty in Artificial Intelligence: Exercises (0.5 ECTS) H00H2a staff staff
Uncertainty in Artificial Intelligence: Project (0.5 ECTS) H08M4a staff staff
4 ECTS Artificial Neural Networks and Deep Learning H02C4A staff staff
Artificial Neural Networks and Deep Learning: Lecture (3 ECTS) H02C4a staff staff
Artificial Neural Networks and Deep Learning: Exercises (1 ECTS) H00G8a staff staff
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ECS Optional Components
Students must select 20 credits from this group or from any other group in the programme. In particular, students can also select courses from the Advanced Mandatory Components of the other two options (SLT or BDA), provided they meet the prerequisites.
Students who did not obtain a credit for a course on Object Oriented Programming in a prior study programme are required to select the course "I0S75A Introduction to Object Oriented Programming" as part of their optional component. The course cannot be selected by students who already obtained a credit for such a course in a prior study programme.4 ECTS Introduction to Object Oriented Programming I0S75A staff staff
- V.van Noort (coordinator)
- G.Baele
- J.Demeulemeester
- V.van Noort
- N.
- P.Lutsik (substitute)
Introduction to Object Oriented Programming: Lectures (2 ECTS) I0S71a staff staff
Introduction to Object Oriented Programming: Exercises (1 ECTS) I0S72a staff staff
- G.Baele
- J.Demeulemeester
- V.van Noort
- N.
- P.Lutsik (substitute)
Introduction to Object Oriented Programming: Project (1 ECTS) I0S73a staff staff
- G.Baele
- J.Demeulemeester
- V.van Noort
- N.
- P.Lutsik (substitute)
4 ECTS Genetic Algorithms and Evolutionary Computing H02D1A staff staff
Genetic Algorithms and Evolutionary Computing: Lecture (1.8 ECTS) H02D1a staff staff
Genetic Algorithms and Evolutionary Computing: Exercises (0.6 ECTS) H00H1a staff staff
Genetic Algorithms and Evolutionary Computing: Project (1.6 ECTS) H08M3a staff staff
4 ECTS Foundations of Formal Theories of Language H02D4A staff- N.
staff
- N.
Foundations of Formal Theories of Language (4 ECTS) H02D4a staff- N.
staff
- N.
4 ECTS Neural Computing H02B3A staff staff
Neural Computing: Lecture (3.5 ECTS) H02B3a staff staff
Neural Computing: Laboratory Sessions (0.5 ECTS) H00G2a staff staff
4 ECTS Multi-Agent Systems H02H4A staff- N.
staff
- N.
Multi-Agent Systems: Lecture (3 ECTS) H02H4a staff- N.
staff
- N.
Multi-Agent Systems: Project (1 ECTS) H08M2a staff- N.
staff
- N.
4 ECTS Cybernetics and its Applications in Physiology and Biological Sciences H02H5A staff staff
Cybernetics and its Applications in Physiology and Biological Sciences (4 ECTS) H02H5a staff staff
4 ECTS Natural Language Processing H02B1A staff staff
Natural Language Processing: Lecture (3.5 ECTS) H02B1a staff staff
Natural Language Processing: Exercises (0.5 ECTS) H00G0a staff staff
4 ECTS Knowledge Representation H02C3A staff staff
Knowledge Representation: Lecture (3.5 ECTS) H02C3a staff staff
Knowledge Representation: Exercises (0.5 ECTS) H00G7a staff staff
4 ECTS Biometrics System Concepts H02C7A staff staff
Biometrics System Concepts: Lecture (3.6 ECTS) H02C7a staff staff
Biometrics Systems Concepts: Exercises (0.4 ECTS) H00I1a staff staff
4 ECTS Information Retrieval and Search Engines H02C8A staff staff
Information Retrieval and Search Engines: Lecture (3 ECTS) H02C8a staff staff
Information Retrieval and Search Engines: Exercises (1 ECTS) H00G9a staff staff
4 ECTS Support Vector Machines: Methods and Applications H02D3A staff staff
Support Vector Machines: Methods and Applications: Lecture (3 ECTS) H02D3a staff staff
Support Vector Machines: Methods and Applications: Exercises (1 ECTS) H00H3a staff staff
4 ECTS Robotics H02A4A staff staff
- H.Bruyninckx (coordinator)
- R.Detry
- N.
- E.Aertbeliën (substitute)
- W.Decré (substitute)
Robotics (4 ECTS) H02A4a staff staff
- H.Bruyninckx
- R.Detry
- N.
- E.Aertbeliën (substitute)
- W.Decré (substitute)
4 ECTS Computer Vision H02A5A staff- N.
- M.Proesmans (substitute)
staff
- N.
- M.Proesmans (substitute)
Computer Vision: Lecture (1.5 ECTS) H02A5a staff- N.
- M.Proesmans (substitute)
staff
- N.
- M.Proesmans (substitute)
Computer Vision: Project (2.5 ECTS) H02K5a staff- N.
- M.Proesmans (substitute)
staff
- N.
- M.Proesmans (substitute)
4 ECTS Bio-informatics H02H6B staff staff
Bio-informatics (4 ECTS) H02H6a staff staff
4 ECTS Topics in Psychonomic Science P0P75A staff staff
- B.Reynvoet (coordinator)
- R.Krampe
- B.Reynvoet
- W.Schaeken
- J.Wagemans
Topics in Psychonomic Science (4 ECTS) P0P75a staff 4 ECTS Brain Computer Interfaces H08M0A staff staff
Brain Computer Interfaces: Lectures (3.5 ECTS) H08M0a staff staff
Brain Computer Interfaces: Exercises (0.5 ECTS) H08M1a staff staff
4 ECTS Analysis of Large Scale Social Networks H0T26A staff staff
Analysis of Large Scale Social Networks: Lectures (2.5 ECTS) H0T26a staff staff
Analysis of Large Scale Social Networks: Exercises (1 ECTS) H0T27a staff staff
Analysis of Large Scale Social Networks: Project (0.5 ECTS) H0T28a staff staff
4 ECTS Reinforcement Learning H0O23A staff staff
Reinforcement Learning: Lecture (3 ECTS) H0O23a staff staff
Reinforcement Learning: Exercises (1 ECTS) H0O24a staff staff
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ECS Master's Thesis
Students are required to make a Master's thesis in a subject related to the ECS knowledge domain.
15 ECTS Master's Thesis ECS H02D6A staff- N.
staff
- N.
Master's Thesis ECS (15 ECTS) H02D6a staff- N.
staff
- N.
-
-
Specialisation: Speech and Language Technology (SLT)
Students follow all subgroups of the option, according to the rules defined in these subgroups.
-
SLT Introductory Components
Students follow the course in the SLT Compulsory Introductory Components subgroup and select 4 credits from the SLT Elective Introductory Components subgroup.
-
SLT Compulsory Introductory Components
Students have to take the courses offered in this group.
4 ECTS Machine Learning and Inductive Inference H02C1A staff staff
Machine Learning and Inductive Inference: Lecture (3 ECTS) H02C1a staff staff
Machine Learning and Inductive Inference: Exercises (1 ECTS) H00G6a staff staff
5 ECTS Fundamentals of Artificial Intelligence H02A0C staff staff
Fundamentals of Artificial Intelligence: Lecture (3 ECTS) H02A0a staff staff
Fundamentals of Artificial Intelligence: Exercises (1 ECTS) H02K1a staff staff
Fundamentals of Artificial Intelligence: Project (1 ECTS) H0O44a staff staff
-
SLT Elective Introductory Components
Students select 4 credits from the courses offered in this group.
4 ECTS Cognitive Science H02B2A staff- W.Schaeken
- H.Stuyck (substitute)
staff
- W.Schaeken
- H.Stuyck (substitute)
Cognitive Science: Lecture (3.5 ECTS) H02B2a staff- W.Schaeken
- H.Stuyck (substitute)
staff
- W.Schaeken
- H.Stuyck (substitute)
Cognitive Science: Exercises (0.5 ECTS) H00G1a staff- W.Schaeken
- H.Stuyck (substitute)
staff
- W.Schaeken
- H.Stuyck (substitute)
4 ECTS Privacy and Big Data H00Y2A staff staff
- R.Gálvez Vizcaíno
- N.
- R.Gálvez Vizcaíno (substitute)
Privacy and Big Data: Lecture (3 ECTS) H00Y2a staff- N.
- R.Gálvez Vizcaíno (substitute)
staff
- N.
- R.Gálvez Vizcaíno (substitute)
Privacy and Big Data: Practical Sessions (1 ECTS) H00Y3a staff staff
4 ECTS Philosophy of Mind and Artificial Intelligence H02D5A staff staff
Philosophy of Mind and Artificial Intelligence (4 ECTS) H02D5a staff staff
4 ECTS AI Ethics & Regulation H0P05A staff- N.
- A.Kuczerawy (substitute)
staff
- N.
- A.Kuczerawy (substitute)
AI Ethics & Regulation: Lecture (4 ECTS) H0P05a staff- N.
- A.Kuczerawy (substitute)
staff
- N.
- A.Kuczerawy (substitute)
-
-
SLT Programming Component
-
SLT Object Oriented Programming
Students who did not obtain a credit for a course on Object Oriented Programming in a prior study program are required to select the course 'H0P66A Scripting Language' as one of their SLT Optional Components.
4 ECTS Scripting Languages H0P66A staff staff
Scripting Languages: Lecture (2 ECTS) H0P66a staff staff
Scripting Languages: Exercises (0.5 ECTS) H0P67a staff staff
Scripting Languages: Projects (1.5 ECTS) H0P68a staff staff
-
-
SLT Advanced Mandatory Components
Students are required to take all courses within this group.
4 ECTS Speech Science H02C9A staff staff
Speech Science: Lecture (3 ECTS) H02C9a staff staff
Speech Science: Exercises (1 ECTS) H00H0a staff staff
4 ECTS Natural Language Processing H02B1A staff staff
Natural Language Processing: Lecture (3.5 ECTS) H02B1a staff staff
Natural Language Processing: Exercises (0.5 ECTS) H00G0a staff staff
4 ECTS Linguistics and Artificial Intelligence H02B6A staff staff
Linguistics and Artificial Intelligence: Lecture (3.5 ECTS) H02B6a staff staff
Linguistics and Artificial Intelligence: Exercises (0.5 ECTS) H00I4a staff staff
4 ECTS Speech Recognition H02A6A staff staff
- H.Van hamme (coordinator)
- D.Van Compernolle
- H.Van hamme
Speech Recognition: Lecture (3 ECTS) H02A6a staff Speech Recognition: Exercises (1 ECTS) H02K6a staff staff
4 ECTS Language Engineering Applications H0T29A staff staff
- T.Van de Cruys (coordinator)
- H.Van hamme
- M.de Lhoneux
- A.van Wieringen
- N.
Language Engineering Applications: Lectures (4 ECTS) H0T29a staff
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SLT Optional Components
Students must select 12 credits from all other components in the program or from any component of the program Master in Digital Humanities.
Students who did not obtain a credit for a course on Object Oriented Programming in a prior study programme are required to select the course 'H0P66A Scripting Languages' as part of their optional component. -
SLT Master's Thesis
Students within the SLT option are required to prepare a Master's thesis in a subject belonging to the SLT knowledge area.
15 ECTS Master's Thesis SLT H02J9B staff- N.
staff
- N.
Master's Thesis SLT (15 ECTS) H02J9a staff- N.
staff
- N.
-
-
Specialisation: Big Data Analytics (BDA)
Students follow all subgroups of the option, according to the rules defined in these subgroups.
-
BDA Introductory Components
Students take all courses in this subgroup.
5 ECTS Fundamentals of Artificial Intelligence H02A0A staff staff
Fundamentals of Artificial Intelligence: Lecture (3 ECTS) H02A0a staff staff
Fundamentals of Artificial Intelligence: Exercises (1 ECTS) H02K1a staff staff
Fundamentals of Artificial Intelligence: Project (1 ECTS) H0O43a staff staff
6 ECTS Data and Statistical Modelling H00Y0A staff- A.Carbonez (coordinator)
- N.
staff
- A.Carbonez (coordinator)
- N.
Data and Statistical Modelling: Extension (0.6 ECTS) H00Y0a staff staff
Data and Statistical Modelling: Extension: Exercises (0.4 ECTS) H00Y1a staff staff
Univariate Data and Modelling (3 ECTS) I0S08a staff staff
Exercises in Univariate Data and Modelling (2 ECTS) I0S11a staff staff
4 ECTS Privacy and Big Data H00Y2A staff staff
- R.Gálvez Vizcaíno
- N.
- R.Gálvez Vizcaíno (substitute)
Privacy and Big Data: Lecture (3 ECTS) H00Y2a staff- N.
- R.Gálvez Vizcaíno (substitute)
staff
- N.
- R.Gálvez Vizcaíno (substitute)
Privacy and Big Data: Practical Sessions (1 ECTS) H00Y3a staff staff
-
BDA Programming Component
All students take the course offered in this subgroup.
-
BDA Advanced Mandatory Components
Students take all courses in this subgroup.
4 ECTS Machine Learning and Inductive Inference H02C1A staff staff
Machine Learning and Inductive Inference: Lecture (3 ECTS) H02C1a staff staff
Machine Learning and Inductive Inference: Exercises (1 ECTS) H00G6a staff staff
4 ECTS Data Mining H02C6A staff staff
Data Mining: Lecture (3.2 ECTS) H02C6a staff staff
Data Mining: Practical Sessions (0.8 ECTS) H00I0a staff staff
-
BDA Optional Components
Students must select 16 credits from this subgroup.
4 ECTS Uncertainty in Artificial Intelligence H02D2A staff staff
- L.De Raedt (coordinator)
- T.De Laet
- L.De Raedt
Uncertainty in Artificial Intelligence: Lecture (3 ECTS) H02D2a staff staff
Uncertainty in Artificial Intelligence: Exercises (0.5 ECTS) H00H2a staff staff
Uncertainty in Artificial Intelligence: Project (0.5 ECTS) H08M4a staff staff
4 ECTS Information Retrieval and Search Engines H02C8A staff staff
Information Retrieval and Search Engines: Lecture (3 ECTS) H02C8a staff staff
Information Retrieval and Search Engines: Exercises (1 ECTS) H00G9a staff staff
4 ECTS Support Vector Machines: Methods and Applications H02D3A staff staff
Support Vector Machines: Methods and Applications: Lecture (3 ECTS) H02D3a staff staff
Support Vector Machines: Methods and Applications: Exercises (1 ECTS) H00H3a staff staff
4 ECTS Computer Vision H02A5A staff- N.
- M.Proesmans (substitute)
staff
- N.
- M.Proesmans (substitute)
Computer Vision: Lecture (1.5 ECTS) H02A5a staff- N.
- M.Proesmans (substitute)
staff
- N.
- M.Proesmans (substitute)
Computer Vision: Project (2.5 ECTS) H02K5a staff- N.
- M.Proesmans (substitute)
staff
- N.
- M.Proesmans (substitute)
4 ECTS Speech Recognition H02A6A staff staff
- H.Van hamme (coordinator)
- D.Van Compernolle
- H.Van hamme
Speech Recognition: Lecture (3 ECTS) H02A6a staff Speech Recognition: Exercises (1 ECTS) H02K6a staff staff
4 ECTS Bio-informatics H02H6B staff staff
Bio-informatics (4 ECTS) H02H6a staff staff
4 ECTS Artificial Neural Networks and Deep Learning H02C4A staff staff
Artificial Neural Networks and Deep Learning: Lecture (3 ECTS) H02C4a staff staff
Artificial Neural Networks and Deep Learning: Exercises (1 ECTS) H00G8a staff staff
4 ECTS AI Ethics & Regulation H0P05A staff- N.
- A.Kuczerawy (substitute)
staff
- N.
- A.Kuczerawy (substitute)
AI Ethics & Regulation: Lecture (4 ECTS) H0P05a staff- N.
- A.Kuczerawy (substitute)
staff
- N.
- A.Kuczerawy (substitute)
4 ECTS Analysis of Large Scale Social Networks H0T26A staff staff
Analysis of Large Scale Social Networks: Lectures (2.5 ECTS) H0T26a staff staff
Analysis of Large Scale Social Networks: Exercises (1 ECTS) H0T27a staff staff
Analysis of Large Scale Social Networks: Project (0.5 ECTS) H0T28a staff staff
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BDA Master's Thesis
Students are required to make a Master's Thesis in a subject related to the BDA knowledge domain.
15 ECTS Master's Thesis BDA H00Y7A staff- N.
staff
- N.
Master's Thesis BDA (15 ECTS) H00Y7a staff- N.
staff
- N.
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-