Artificial Intelligence MSc Vrije Universiteit Amsterdam - Faculteit der Exacte Wetenschappen - M Artificial Intelligence

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1 Artificial Intelligence MSc Vrije Universiteit Amsterdam - - M Artificial Intelligence Vrije Universiteit Amsterdam - - M Artificial Intelligence I

2 Studiegids informatie voor de masteropleiding Artificial Intelligence. Klik op de onderstaande links om informatie over de vakken te bekijken. Of download de volledige studiegids als pdf met de knop Maak pdf van gehele opleiding. Vrije Universiteit Amsterdam - - M Artificial Intelligence II

3 Inhoudsopgave C-variant Artificial Intelligence and Communications 1 Communication Specialisation 1 Students can opt for an internship of 30 credits (EC), or for a combination of an internship of 21 credits and a thesis of 9 credits. Students can opt for a selection of modules from this group. The following modules are compulsary: - Research Methods (AM_470582) - Science and Communication (AM_470587) Individuele vakken 2 AI C-variant Artificial Intelligence and Communications Optional Courses 2 Artificial Intelligence and Communications Compulsory Courses AI-Part 3 Research variant Knowledge Technology and Intelligent Internet Applications 3 Individuele vakken 4 Recommended optional courses. 4 Compulsory Courses 5 Research variant Cognitive Science 5 Individuele vakken 5 Masterproject 5 Recommended Optional Courses 6 Compulsory Courses 6 Research Variant Computational Intelligence and Selforganisation 7 Individuele vakken 8 Recommended Optional Courses 8 Compulsory Courses 8 Research variant TAI 9 Individuele vakken 9 Compulsory Optional course (Software Engineering) 10 Recommended Optional Courses 10 Compulsory Courses 10 Research Variant Human Ambience 11 Individuele vakken 12 Keuzevakken 12 Optional courses Health 12 Compulsory Courses 12 Vak: Advanced Information Retrieval 13 Vak: Advanced Logic 13 Vak: Advanced Selforganisation 13 Vak: Advanced Statistics for Experimentation 14 Vak: Automated Reasoning in AI 15 Vak: Behavioral Methods 16 Vak: Behaviour Dynamics 16 Vak: Bioinformatics of Large Systems 17 Vak: Brain Imaging 18 Vak: Business Intelligence 18 Vak: Cluster and Grid Computing Vrije Universiteit Amsterdam - - M Artificial Intelligence III

4 Vak: Communication, Organization and Management 21 Vak: Computational Genomics and Proteomics 22 Vak: Data Mining Techniques 22 Vak: Design of Multi-Agent Systems 23 Vak: Design of Multi-Agent Systems Practical 24 Vak: Distributed Algorithms 25 Vak: Distributed Systems 25 Vak: E-Business Innovation 25 Vak: Evolutionaire genetica 26 Vak: Evolutionary Computing 27 Vak: FEW individueel vak intern 28 Vak: Game Theory [MC] 28 Vak: Health Promotion and Disease Prevention 28 Vak: Health Psychology 29 Vak: Human Ambience Innovation 30 Vak: Human Information Processing 31 Vak: Information Retrieval 31 Vak: Information Retrieval (UvA) 32 Vak: Intelligent Web Applications 32 Vak: Intelligent Web Applications 33 Vak: Interactive communication 33 Vak: Internet programming 34 Vak: Internship Communication Specialisation 35 Vak: Internship Communication Specialisation 35 Vak: Interpersonal Communication 35 Vak: Knowledge Management and Modeling 36 Vak: Literature Study 37 Vak: Master Project 38 Vak: Master Project AI for the C-variant 39 Vak: Master Thesis: Research Project Cognitive Science 39 Vak: Memory and Memory Disorders 40 Vak: Mini Master Project AI 40 Vak: Model-based Intelligent Environments 41 Vak: Multimedia Authoring 41 Vak: Multimedia Authoring 41 Vak: Neural Models of Cognitive Processes 42 Vak: Neurale Netwerken 43 Vak: Ontology Engineering 43 Vak: Perception 44 Vak: Prevention of Mental Health Problems 44 Vak: Protocol Validation 45 Vak: Qualitative and Quantitative Research Methods 45 Vak: Research methods 47 Vak: Review Paper 48 Vak: Science and Communication 49 Vrije Universiteit Amsterdam - - M Artificial Intelligence IV

5 Vak: Science Communication through Museums 50 Vak: Science in Dialogue 51 Vak: Science Journalism 52 Vak: Scientific Writing in 53 Vak: Seminar Attention 55 Vak: Seminar Cognitive Neuroscience 56 Vak: Service Oriented Design 57 Vak: Software Architecture 57 Vak: Software Mining 58 Vak: Special Topics Cognitive Science 59 Vak: Statistical Data Analysis 59 Vak: Thinking and Deciding 60 Vak: Voortgezette logica 61 Vrije Universiteit Amsterdam - - M Artificial Intelligence V

6 C-variant Artificial Intelligence and Communications This variant is intended for students in Artificial Intelligence who want to specialize in communication. The programme consists of two parts of 60 cp each, both including their own project with master thesis: one part is dedicated to training in Artificial Intelligence at the master level, the other part is dedicated to communication and is shared with students with other BSc degrees. It focuses on science communication theory and research as well as on science communication in practice. This includes science journalism as well as museology. the use of internet for science communication and health communication. Note: Every programme, including the choice of optional courses, has to be discussed and agreed upon with the master coordinator or a personal mentor and approved by the Examination Board. Opleidingsdelen: Communication Specialisation Individuele vakken AI C-variant Artificial Intelligence and Communications Optional Courses Artificial Intelligence and Communications Compulsory Courses AI-Part Communication Specialisation This specialisation is intended for students with a BSc degree in any of the Bèta-studies who want to specialise in communication. The programme focuses on science communication theory, research and practice. The programme of the communication (C) specialisation is 1 year (54-57 credits). The specialisation must be combined with a specialisation in biological or biomedical research and may not be combined with the Societal specialisation or the Educational specialisation. C-courses are shared with master students of the School of Earth and Environmental Sciences, and of the of Exact Sciences. The communication programme consists of credits. Two courses (12 credits), one research project (21 credits) and a thesis (9 credits) are compulsory. The rest of the program can be filled in with optional courses (1-15 credits). You can do an internship at the department of Science Communication, another research institute, or at a radio station, a newspaper, a museum or another public communication institute, according to your personal interest. Please note that the extent of the internship or research project is 21 credits, which differs from the regular credits for internships and research projects in the other specialisations within the Master's programme Biology. The thesis (9 credits) consists of a study of literature on an aspect of science communication. The thesis consists of a study of literature on an aspect of science communication. The course language is, but the courses Interpersonal Communication, Science Journalism and Science Communication through Museums are taught in Dutch. Programme components: - Internship Science Communication Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 1 van 61

7 - Course modules Communication spec. Students can opt for an internship of 30 credits (EC), or for a combination of an internship of 21 credits and a thesis of 9 credits. Vakken: Naam Periode Credits Code Internship Communication Specialisation Internship Communication Specialisation 0.0 AM_471148nr Semester AM_ Students can opt for a selection of modules from this group. The following modules are compulsary: - Research Methods (AM_470582) - Science and Communication (AM_470587) Vakken: Naam Periode Credits Code Communication, Organization and Management Individuele vakken Period AM_ Interactive communication Period AM_ Interpersonal Communication Qualitative and Quantitative Research Methods Science and Communication Science Communication through Museums Period AM_ Period AM_ Period AM_ Period AM_ Science in Dialogue 6.0 AM_1002 Science Journalism Period AM_ Vakken: Naam Periode Credits Code FEW individueel vak intern 6.0 X_INDVAKI_09 AI C-variant Artificial Intelligence and Communications Optional Courses Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 2 van 61

8 Optional courses to complete 60 cp. Vakken: Naam Periode Credits Code Advanced Logic Periode X_ Automated Reasoning in AI Period X_ Behaviour Dynamics Periode X_ Data Mining Techniques Period X_ Information Retrieval Period X_ Mini Master Project AI Ac. Year (September) 6.0 X_ Voortgezette logica 4.0 X_ Artificial Intelligence and Communications Compulsory Courses AI-Part Compulsory alongside the mentioned courses are optional courses for 39 Ec to complete 60 Ec. Note: Every programme, including the choice of optional courses, has to be discussed and agreed upon with the master coordinator or a personal mentor and approved by the Examination Board. Vakken: Naam Periode Credits Code Master Project AI for the C- variant Ac. Jaar (september) 21.0 X_ Research variant Knowledge Technology and Intelligent Internet Applications This programme contains elements so that the graduate student has a good overview of the contemporary literature regarding applications of intelligent web-sites and intelligent agents on the internet. Furthermore, the student learns techniques and methods from Artificial Intelligence that are used in internet applications. The master graduate student is a capable designer of intelligent web-sites, and applications based on intelligent agents. The student ensures that his/her designs respect the needs of the company for which the design is meant. An increasingly number of companies starts to document knowledge in the company with the use of knowledge acquisition and knowledge modeling techniques from AI. By doing this, the conduct of business is being simplified. Also with change processes in companies, automated knowledge intensive methods can be used, together with elements from economics and organisation psychology. For graduates, these is a multi-disciplinary field of labour. Via company internships and company funded research projects there is good contact with industry. Audience: students with an interest in analysing, modelling, simulating and experimenting with dynamics properties. The progamme consists of 120 credits - compulsory courses 69 credits (including a Master Project of 30 Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 3 van 61

9 credits) - optional courses 51 credits Note: Every programme, including the choice of optional courses, has to be discussed and agreed upon with the master coordinator or a personal mentor and approved by the Examination Board. Master s: Dr. M. Hoogendoorn K room T-320a T +31 (0) E Dr. S. Schlobach (International students) K room T-365 T +31 (0) E Opleidingsdelen: Individuele vakken Recommended optional courses. Compulsory Courses Individuele vakken Vakken: Naam Periode Credits Code FEW individueel vak intern 6.0 X_INDVAKI_09 Recommended optional courses. Vakken: Naam Periode Credits Code Advanced Logic Periode X_ Automated Reasoning in AI Period X_ Data Mining Techniques Period X_ E-Business Innovation Periode X_ Game Theory [MC] Periode X_ Internet programming 6.0 X_ Mini Master Project AI Ac. Year (September) 6.0 X_ Multimedia Authoring Periode X_ Multimedia Authoring Periode X_ Protocol Validation 6.0 X_ Service Oriented Design Periode X_ Voortgezette logica 4.0 X_ Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 4 van 61

10 Compulsory Courses Compulsory alongside the mentioned courses, are optional courses (51 credits) to complete 120 credits. Note: Every programme, including the choice of optional courses, has to be discussed and agreed upon with the master coordinator or a personal mentor and approved by the Examination Board. Vakken: Naam Periode Credits Code Advanced Information Retrieval Research variant Cognitive Science Semester X_ Behaviour Dynamics Periode X_ Evolutionary Computing Period X_ Intelligent Web Applications Periode X_ Knowledge Management and Modeling Period X_ Master Project Semester X_ Ontology Engineering Period X_ Research methods 6.0 X_ Scientific Writing in Periode 2, Periode 3, Periode 4, Periode X_ Opleidingsdelen: Individuele vakken Masterproject Recommended Optional Courses Compulsory Courses Individuele vakken Vakken: Naam Periode Credits Code FEW individueel vak intern 6.0 X_INDVAKI_09 Masterproject Students need to select one of the mentioned Master Projects. Note: Every programme, including the choice of optional courses, has to be discussed and agreed upon with the master coordinator or a personal Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 5 van 61

11 mentor and approved by the Examination Board. Vakken: Naam Periode Credits Code Master Project Semester X_ Master Thesis: Research Project Cognitive Science Recommended Optional Courses Semester P_MTHRCSC Vakken: Naam Periode Credits Code Advanced Selforganisation Period X_ Advanced Statistics for Experimentation Design of Multi-Agent Systems Compulsory Courses Period P_MADVSTA Periode X_ Internet programming 6.0 X_ Memory and Memory Disorders Period P_MMEMORY Mini Master Project AI Ac. Year (September) 6.0 X_ Perception Period P_MPERCEP Review Paper Period P_MREVPAP Compulsory alongside the mentioned courses, are optional courses (18 credits) to complete 120 credits. Note: Every programme, including the choice of optional courses, has to be discussed and agreed upon with the master coordinator or a personal mentor and approved by the Examination Board. Vakken: Naam Periode Credits Code Behavioral Methods Period P_MBEHMET Behaviour Dynamics Periode X_ Brain Imaging Period P_MBRIMAG Evolutionary Computing Period X_ Human Information Processing Knowledge Management and Modeling Period P_MHINFOP Period X_ Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 6 van 61

12 Neural Models of Cognitive Processes 6.0 P_MNEUMOD Research methods 6.0 X_ Scientific Writing in Periode 2, Periode 3, Periode 4, Periode X_ Seminar Attention Period P_MSEMATT Seminar Cognitive Neuroscience Special Topics Cognitive Science Period 1, Period P_MSEMCNS Ac. Year (September) 9.0 X_ Thinking and Deciding Period P_MTHIDEC Research Variant Computational Intelligence and Selforganisation After completion of this Master programme, the student - has an overview of the literature an practice in the area of organisation dynamics and self organisation - has mastered methods and techniques for modelling various types of organisations and their dynamics - is capable of constructing models of dynamic organisations with which can be simulated and experimented - is capable of conducting application-directed AI research in combination with other fields of research. Students of this programme can function in industry through a variety of different often management-related professions, within a diversity of institutions and companies, for example, in strategic management and organisation advising. Audience: Students with an interest in analysing, modelling, simulating and experimenting with dynamics properties. The progamme consists of 120 credits - compulsory courses 69 credits (including a Master Project of 30 credits) - optional courses 51 credits Note: Every programme, including the choice of optional courses, has to be discussed and agreed upon with the master coordinator or a personal mentor and approved by the Examination Board. Master s: Dr. M. Hoogendoorn K room T-320a T +31 (0) E Dr. S. Schlobach (International students) K room T-365 T +31 (0) E Opleidingsdelen: - Individuele vakken Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 7 van 61

13 - - Recommended Optional Courses Compulsory Courses Individuele vakken Vakken: Naam Periode Credits Code FEW individueel vak intern 6.0 X_INDVAKI_09 Recommended Optional Courses Vakken: Naam Periode Credits Code Bioinformatics of Large Systems Compulsory Courses Periode X_ Business Intelligence Period E_BK3_BI Cluster and Grid Computing Period X_ Computational Genomics and Proteomics 6.0 X_ Distributed Algorithms Period X_ Distributed Systems Periode X_ Evolutionaire genetica Periode AB_ Game Theory [MC] Periode X_ Intelligent Web Applications 8.0 X_ Internet programming 6.0 X_ Mini Master Project AI Ac. Year (September) 6.0 X_ Ontology Engineering Period X_ Statistical Data Analysis Period X_ Compulsory alongside the mentioned courses, are optional courses (51 credits) to complete 120 credits. Note: Every programme, including the choice of optional courses, has to be discussed and agreed upon with the master coordinator or a personal mentor and approved by the Examination Board. Vakken: Naam Periode Credits Code Advanced Selforganisation Period X_ Behaviour Dynamics Periode X_ Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 8 van 61

14 Data Mining Techniques Period X_ Evolutionary Computing Period X_ Knowledge Management and Modeling Research variant TAI Period X_ Master Project Semester X_ Research methods 6.0 X_ Scientific Writing in Periode 2, Periode 3, Periode 4, Periode X_ The graduate student of this Master programme is capable of applying techniques from Computer Science to problems of an Artificial Intelligence nature, e.g., designing knowledge-based systems or multiagent systems. This technically adapt graduate, furthermore, has learned proven AI techniques in the areas of machine learning, neural networks, knowledge representation, and evolutionary computing. Graduate students are well equiped for work in companies that create intelligent applications. Audience: the programme aims at students with a Bachelor in Computer Science, having an interest in Artificial Intelligence. The progamme consists of 120 credits - compulsory courses 78 credits (including a Master Project of 30 credits) - compulsory optional choice 6 credits - optional courses 36 credits Note: Every programme, including the choice of optional courses, has to be discussed and agreed upon with the master coordinator or a personal mentor and approved by the Examination Board. Master s: Dr. M. Hoogendoorn K room T-320a T +31 (0) E Dr. S. Schlobach (International students) K room T-365 T +31 (0) E Opleidingsdelen: Individuele vakken Compulsory Optional course (Software Engineering) Recommended Optional Courses Compulsory Courses Individuele vakken Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 9 van 61

15 Vakken: Naam Periode Credits Code FEW individueel vak intern 6.0 X_INDVAKI_09 Compulsory Optional course (Software Engineering) Students need to select at least one out of the following courses. Note: Every programme, including the choice of optional courses, has to be discussed and agreed upon with the master coordinator or a personal mentor and approved by the Examination Board. Vakken: Naam Periode Credits Code Service Oriented Design Periode X_ Software Architecture Period X_ Software Mining Period X_ Recommended Optional Courses Vakken: Naam Periode Credits Code Advanced Logic Periode X_ Automated Reasoning in AI Period X_ Data Mining Techniques Period X_ Information Retrieval Period X_ Information Retrieval (UvA) 6.0 X_ Internet programming 6.0 X_ Mini Master Project AI Ac. Year (September) 6.0 X_ Voortgezette logica 4.0 X_ Compulsory Courses Compulsory alongside the mentioned courses, are optional courses (36 credits) to complete 120 credits. Note: Every programme, including the choice of optional courses, has to be discussed and agreed upon with the master coordinator or a personal mentor and approved by the Examination Board. Vakken: Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 10 van 61

16 Naam Periode Credits Code Behaviour Dynamics Periode X_ Distributed Systems Periode X_ Evolutionary Computing Period X_ Intelligent Web Applications Periode X_ Knowledge Management and Modeling Research Variant Human Ambience Period X_ Literature Study Ac. Year (September) 6.0 X_ Master Project Semester X_ Neurale Netwerken Periode X_ Research methods 6.0 X_ Scientific Writing in Periode 2, Periode 3, Periode 4, Periode X_ In the Master variant Human Ambience you learn on a detailed level how to model both mental and physiological processes of human functioning. For instance, you can learn how to model the mental and physical states associated with depression. Such models are then used in applications that support humans in their daily lives in a dedicated manner, also to enable the developed support systems to understand humans better. In the specialization phase of the master you can study relevant courses with respect to an application area (e.g. support of people during exercising, or elderly care) or a relevant scientific discipline (e.g. psychology, sociology, movement sciences, biomedical sciences, criminology, etc.). During you final Master project you will then combine your domain knowledge with the knowledge of modeling such human processes. The progamme consists of 120 credits - compulsory courses 66 credits (including a Master Project of 30 credits) - optional courses 54 credits Note: Every programme, including the choice of optional courses, has to be discussed and agreed upon with the master coordinator or a personal mentor and approved by the Examination Board. Master s: Dr. M. Hoogendoorn K room T-320a T +31 (0) E Dr. S. Schlobach (International students) K room T-365 T +31 (0) E Opleidingsdelen: - - Individuele vakken Keuzevakken Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 11 van 61

17 - - Optional courses Health Compulsory Courses Individuele vakken Vakken: Naam Periode Credits Code FEW individueel vak intern 6.0 X_INDVAKI_09 Keuzevakken N.B. Students can compose an individual programme by selecting all optional courses from one specific discipline, but also by combining courses from different disciplines, which have a common application. Vakken: Naam Periode Credits Code Advanced Selforganisation Period X_ Design of Multi-Agent Systems Practical Optional courses Health Period X_ Mini Master Project AI Ac. Year (September) 6.0 X_ Vakken: Naam Periode Credits Code Health Promotion and Disease Prevention Compulsory Courses Period AM_ Health Psychology Period AM_ Prevention of Mental Health Problems Period AM_ Compulsory alongside the mentioned courses, are optional courses (54 credits) to complete 120 credits. Note: Every programme, including the choice of optional courses, has to be discussed and agreed upon with the master coordinator or a personal mentor and approved by the Examination Board. Vakken: Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 12 van 61

18 Naam Periode Credits Code Behaviour Dynamics Periode X_ Evolutionary Computing Period X_ Human Ambience Innovation Knowledge Management and Modeling Advanced Information Retrieval Periode X_ Period X_ Master Project Semester X_ Model-based Intelligent Environments 6.0 X_ Research methods 6.0 X_ Scientific Writing in Periode 2, Periode 3, Periode 4, Periode X_ Vakcode X_ (418043) Periode Semester 2 Voertaal Engels Faculteit Advanced Logic Vakcode X_ (405048) Periode Periode 4 Voertaal Engels Faculteit Coördinator dr. R.D.A. Hendriks Docent(en) dr. R.D.A. Hendriks Lesmethode(n) Hoorcollege, Werkcollege Doelgroep mai-ktiia, mai-tli, mai-c-var, mcs-fmsv Advanced Selforganisation Course code X_ (400434) Period Period 2 dr. M.C. Schut dr. M.C. Schut Lecture Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 13 van 61

19 To understand, simulate and analyse the behaviour and self-organization of complex systems. The student is able to explain, implement and recognize basic principles and properties of such systems. Theory in lectures and practice in labs. Report including description of simulation and experimental analysis. Course reading Schut M.C., Scientific Handbook for Simulation of Collective Intelligence, Available at collectivae. net/. Target group mai (computational intelligence and self organisation), mbmi, mis, mcs Remarks More information available on BlackBoard. This is a project- oriented course and therefore students will be expected to have basic programming skills. Advanced Statistics for Experimentation Course code P_MADVSTA (815097) Period Period 4 Faculteit der Psychologie en Pedagogiek dr. M. Meeter Lecture To acquire knowledge of and insight into statistics in order to be able to apply these techniques and read associated literature at a level relevant for research in cognitive neuropsychology. Statistics: the General Linear Model. Lectures and practicals Assignments and final examination. Course reading To be announced. Remarks Admission conditions: Statistics (or a similar course). Teacher: dr. M. Gallucci. Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 14 van 61

20 Automated Reasoning in AI Course code X_ (400389) Period Period 5 dr. K.S. Schlobach dr. A.C.M. ten Teije, dr. K.S. Schlobach Lecture, Seminar Since its early days Artificial Intelligence has employed logic as a mean to provide generic solutions for computationally and conceptually difficult practical problems. The aim of the course is to make the students familiar with a number of popular logic- based representation and reasoning mechanisms for Artificial Intelligence. Furthermore, students should have the capability to transfer the learned techniques to other problems and to other representation mechanisms. The course will be structured in three modules. In each of these modules a practical problem will be introduced, a logic- based representation proposed, and the basic techniques for automated reasoning in this language studied in a practical, hands on, way. In a nutshell, we plan to cover: - propositional Logic for scheduling, and satisfiability checking with Davis Putnam; - Allen's interval logic for Planning, with constraint propagation in Temporal Constraint Networks; - description logics for classification, with Tableau calculi for subsumption. In period 5 there will be lectures and practical sessions, plus significant time for self- study and practical work. In period 6 there will be regular meetings to support for the work on a larger project. 3 practical assignments Course reading Selected scientific papers. Entry requirements Basic knowledge in logic is an advantage, but not required, as is some familiarity with programming. Target group mai Remarks Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 15 van 61

21 For further information see the AR in AI blackboard site. Behavioral Methods Course code P_MBEHMET (815096) Period Period 3 Faculteit der Psychologie en Pedagogiek dr. L.J.F.M. van Zoest dr. L.J.F.M. van Zoest, dr. A.V. Belopolskiy Lecture To provide students with in- depth knowledge of the strengths and weaknesses of the scientific method and behavioural methods commonly used in cognitive (neuro) psychology. This course reviews the basic principles that govern the development and evaluation of scientific theories (e. g. philosophy of science). Commonly used experimental methods and methods for data analysis are discussed and evaluated. The methods that are covered in detail include: method for discovering processing stages, signal detection theory, various psychophysical methods, and methods used in cognitive neuropsychology (e. g. double dissociations. Traditional; dataanalysis methods, such as general linear model and null- hypothesis significance testing are also discussed, as well as their alternatives. Lectures + assignments. open- ended written examination. Course reading A selection of articles and bookchapters. Behaviour Dynamics Vakcode X_ (400113) Periode Periode 1+2 Voertaal Engels Faculteit Coördinator dr. O. Sharpanskykh Docent(en) dr. O. Sharpanskykh Lesmethode(n) Hoorcollege Doel vak To learn how to identify, specify and predict different types of behaviour; to understand how externally observable behaviour emerges Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 16 van 61

22 from internal mechanisms; to be able to construct computational behavioural models and to perform analysis based on these models using software tools Bioinformatics of Large Systems Vakcode X_ (405063) Periode Periode 5 Voertaal Engels Faculteit Doel vak A theoretical and practical bioinformatics course on computational methods in proteomics, genomics, gene regulation, signalling, microarray experiments, protein-protein interactions, and data-mining. Goals: - At the end of the course, students will be aware of the issues, methodology and available bioinformatics tools, so to become a creative bioinformatics problem solver and tools creator. - At the end of the course, students will have hands-on experience in handling large biological datasets. Inhoud vak Theory: - proteomics (mass spectrometry), genomics, gene regulation, signalling, microarray experiments, protein-protein interactions, and data-mining, next-generation sequencing, pattern recognition, ontologies, and GRID computing, Petri nets. Practical: - Assignment biological data clustering (in R) - Assignment Gene regulation / Signalling network modelling using Petri nets. - Assignment Pattern detection - Assignment PPI networks Onderwijsvorm 13 Lectures (4 two-hour lectures per week); 6 computer practicals (2 two-hour sessions per week). Toetsvorm Assignment results and oral or written exam (depending on number of course students). Literatuur Course material on bb.vu.nl Marketa Zvelebil and Jeremy O. Baum Understanding Bioinformatics Garland Science 2008 ISBN-10: Vereiste voorkennis Bachelor in any science discipline (including medicine), or third-year BSc students. Basic programming skills (R) and an interest in biological problems. Vrije Universiteit Amsterdam - - M Artificial Intelligence Pagina 17 van 61

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