The student should acquire basic theoretical and practical knowledge and principles used in mathematical modeling of physical processes.

Upon successful completion of the course, students will be able to: - explain the basic principles of numerical solution of equations that describe the considered physical phenomena and processes.

1. Physical and mathematical phenomenon and process. 2. Models of linear and non-linear oscillatory systems. 3. Van der Pol oscillator. 4. Lorentz equations. 5. Problems of stationary and non-stationary heat conduction. 6. Wave equation. 7. Burger's equation.

1. Model formation, software implementation. 2. Analysis and discussion of the obtained results. 3. Implementation of algorithms in Python. 4. Software for visualization of results (Paraview).

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Total assigned hours: 75

New material: 20
Elaboration and examples (recapitulation): 10

Auditory exercises: 20
Laboratory exercises: 0
Calculation tasks: 5
Seminar paper: 0
Project: 0
Consultations: 0
Discussion/workshop: 5
Research study work: 0

Review and grading of calculation tasks: 0
Review and grading of lab reports: 0
Review and grading of seminar papers: 0
Review and grading of the project: 0
Test: 5
Test: 5
Final exam: 5

Activity during lectures: 0
Test/test: 0
Laboratory practice: 0
Calculation tasks: 20
Seminar paper: 0
Project: 50
Final exam: 30
Requirement for taking the exam (required number of points): 0

D. Acheson, "From calculus to chaos," Oxford University Press, 1997.; D. G. Zill, "A first course in differential equations with modelling applications," Brooks/Cole, 2013