| Course title | Stochastic processes |
|---|---|
| Course code | SLO/PGSSP |
| Organizational form of instruction | Lecture |
| Level of course | Doctoral |
| Year of study | not specified |
| Semester | Winter and summer |
| Number of ECTS credits | 20 |
| Language of instruction | Czech, English |
| Status of course | unspecified |
| Form of instruction | Face-to-face |
| Work placements | This is not an internship |
| Recommended optional programme components | None |
| Lecturer(s) |
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| Course content |
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1. Random variables. 2. Random processes. 3. Stochastic processes. 4. Markovian processes. 5. Markovian chains. 6 - 9. Master equations. 10 - 11. One-step processes.
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| Learning activities and teaching methods |
Lecture
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| Learning outcomes |
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The lecture presents an exposition of the stochastic processes from a physicist's viewpoint.
Knowledge. Define main notions, approaches, to be able to solve model problems. |
| Prerequisites |
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Basic knowledge of the undergraduate mathematics and physics.
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| Assessment methods and criteria |
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Oral exam
Basic knowledge of mathematics. |
| Recommended literature |
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| Study plans that include the course |
| Faculty | Study plan (Version) | Category of Branch/Specialization | Recommended semester |
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