| Language of instruction : English |
| Exam contract: not possible |
|
Sequentiality
|
| |
|
Mandatory sequentiality bound on the level of programme components
|
| |
| |
| |
Following programme components must have been included in your study programme in a previous education period
|
| |
|
Probability theory and statistics (2941)
|
6.0 stptn |
| |
|
| Degree programme | | Study hours | Credits | P1 SBU | P1 SP | 2nd Chance Exam1 | Tolerance2 | Final grade3 | |
 | Master Computer Science profile Artificial Intelligence | 2-yearly compulsory (current academic year) | 162 | 6,0 | 162 | 6,0 | Yes | Yes | Numerical |  |
|
| | | Learning outcomes |
- EC
| EC 1: A graduate of the Master of Computer Science programme has insight into the most important technological developments in the field of computer science and the underlying scientific principles. | - EC
| EC 4: A graduate of the Master of Computer Science programme takes account of the limitations of computer science, such as the existence of undecidedness and the existence of important unresolved problems in computer science such as the P=NP problem. | - EC
| EC 9: A graduate of the Master of Computer Science programme is able to clearly report both orally and verbally on his or her work in a national and international context. | - EC
| EC 10: A graduate of the Master of Computer Science programme is able to work in team; he or she is able to distribute and coordinate the activities through cooperation in small and large groups. |
|
| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
|
|
·Heuristics for searching in a large space of solutions
.Planning
·Knowledge representation
.Logic programming
·SAT solving
·Probabilistic reasoning
·Neural networks
·Reinforcement learning
·Natural language processing
·Philosophical and societal aspects of AI.
The course does not address topics related to learning from data (data mining, machine learning), as existing courses already deal with these topics.
|
|
|
|
|
|
|
|
|
Lecture ✔
|
|
|
|
Response lecture ✔
|
|
|
|
Period 1 Credits 6,00
| Evaluation method | |
|
| Oral evaluation during teaching period | 30 % |
|
|
|
|
|
Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Compulsory textbooks (bookshop) |
| |
Artificial Intelligence : A Modern Approach,S. Russell & P. Norvig,Fourth Edition,Pearson |
|
|
|
|
|
| Master of Computer Science choice | 2-yearly optional (current academic year) | 162 | 6,0 | 162 | 6,0 | Yes | Yes | Numerical | |
|
| | | Learning outcomes |
- EC
| EC 1: A graduate of the Master of Computer Science programme has insight into the most important technological developments in the field of computer science and the underlying scientific principles. | - EC
| EC 4: A graduate of the Master of Computer Science programme takes account of the limitations of computer science, such as the existence of undecidedness and the existence of important unresolved problems in computer science such as the P=NP problem. | - EC
| EC 9: A graduate of the Master of Computer Science programme is able to clearly report both orally and verbally on his or her work in a national and international context. | - EC
| EC 10: A graduate of the Master of Computer Science programme is able to work in team; he or she is able to distribute and coordinate the activities through cooperation in small and large groups. |
|
| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
|
|
·Heuristics for searching in a large space of solutions
.Planning
·Knowledge representation
.Logic programming
·SAT solving
·Probabilistic reasoning
·Neural networks
·Reinforcement learning
·Natural language processing
·Philosophical and societal aspects of AI.
The course does not address topics related to learning from data (data mining, machine learning), as existing courses already deal with these topics.
|
|
|
|
|
|
|
|
|
Lecture ✔
|
|
|
|
Response lecture ✔
|
|
|
|
Period 1 Credits 6,00
| Evaluation method | |
|
| Oral evaluation during teaching period | 30 % |
|
|
|
|
|
Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Compulsory textbooks (bookshop) |
| |
Artificial Intelligence : A Modern Approach,S. Russell & P. Norvig,Fourth Edition,Pearson |
|
|
|
|
|
1 Education, Examination and Legal Position Regulations art.12.2, section 2. |
| 2 Education, Examination and Legal Position Regulations art.16.9, section 2. |
3 Education, Examination and Legal Position Regulations art.15.1, section 3.
|
| Legend |
| SBU : course load | SP : ECTS | N : Dutch | E : English |
|