Applied Discrete Modelling
(in German: Applied Discrete Modelling )
Module-ID: FIN-INF-120279 |
| Link: | LSF |
| Responsibility: | PD Dr. Claudia Krull |
| Lecturer: | PD Dr. Claudia Krull |
| Classes: |
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| Applicability in curriculum: | - M.Sc. INF: Informatik - M.Sc. INGINF: Informatik - M.Sc. WIF: Informatik - M.Sc. DKE: Learning Methods and Models for Data Science - M.Sc. DE: Fachliche Spezialisierung - M.Sc. VC: Computer Science |
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Abbreviation ADM |
Credit Points 6 |
Semester Winter |
Term ab 1. |
Duration 1 Semester |
Language english |
Level Master |
Intended learning outcomes:
- Students understand the basics of Markov chains and know selected applications and solution methods
- Students understand non-Markovian stochastic processes and can model and simulate them in different ways
- Students understand hidden Markovian and non-Markovian processes
- Students know selected research topics of the research group
- Students can implement the models and methods they have learned and apply them to problems from the university's main research areas, in particular medicine and engineering
Content:
- Discrete-time and continuous-time Markov chains
- Applications and implementation of solution methods for Markov chains
- Method of supplementary variables
- Proxel simulation and phase distributions
- Modeling with hidden models
- Programming solution methods for different model classes
- Modeling and solving problems from medicine and engineering
Workload:
56 h lectures and exercise classes
124 h independent work
| Pre-examination requirements: | Type of examination: | Teaching method / lecture hours per week (SWS): |
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Solutions to Assignments 1-6 need to be handed in before the exam registration. |
Oral Exam 30 Minutes |
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| Prerequisites according to examination regulations: | Recommended prerequisites: |
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none |
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| Media: | Literature: |
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recorded lectures and exercises are available |
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Comments: