Kaisa_2012_3_photo by Veikko Somerpuro

Updated course information including handouts will be available at
https://wiki.helsinki.fi/display/mathphys/TCM310%2C+Stochastic+Methods

This page will NOT be maintained by the lecturer.

Student intending to take the form are kindly requested to fill the form at

http://elomake.helsinki.fi/lomakkeet/99573/lomake.html

Filling the form is optional and has no evaluation purpose. It will help the lecturer to better calibrate the course content on students' needs and expectations.

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Paolo Muratore-Ginanneschi's picture

Paolo Muratore-Ginanneschi

Published, 26.8.2019 at 14:50

Please refer to the wiki web-page

https://wiki.helsinki.fi/display/mathphys/TCM310%2C+Stochastic+Methods

for updated info about the course.

Timetable

Here is the course’s teaching schedule. Check the description for possible other schedules.

DateTimeLocation
Tue 3.9.2019
10:15 - 12:00
Fri 6.9.2019
10:15 - 12:00
Tue 10.9.2019
10:15 - 12:00
Fri 13.9.2019
10:15 - 12:00
Tue 17.9.2019
10:15 - 12:00
Fri 20.9.2019
10:15 - 12:00
Tue 24.9.2019
10:15 - 12:00
Fri 27.9.2019
10:15 - 12:00
Tue 1.10.2019
10:15 - 12:00
Fri 4.10.2019
10:15 - 12:00
Tue 8.10.2019
10:15 - 12:00
Fri 11.10.2019
10:15 - 12:00
Tue 15.10.2019
10:15 - 12:00
Fri 18.10.2019
10:15 - 12:00
Thu 24.10.2019
14:15 - 16:00
Tue 29.10.2019
10:15 - 12:00
Fri 1.11.2019
10:15 - 12:00
Tue 5.11.2019
10:15 - 12:00
Fri 8.11.2019
10:15 - 12:00
Tue 12.11.2019
10:15 - 12:00
Fri 15.11.2019
10:15 - 12:00
Tue 19.11.2019
10:15 - 12:00
Fri 22.11.2019
10:15 - 12:00
Tue 26.11.2019
10:15 - 12:00
Fri 29.11.2019
10:15 - 12:00
Tue 3.12.2019
10:15 - 12:00
Tue 10.12.2019
10:15 - 12:00
Fri 13.12.2019
10:15 - 12:00
Mon 16.12.2019
13:15 - 17:00

Other teaching

04.09.2019 Wed 12.15-14.00
11.09.2019 Wed 12.15-14.00
18.09. - 16.10.2019 Wed 12.15-14.00
30.10. - 11.12.2019 Wed 12.15-14.00
Teaching language: English

Description

Master’s Programme in Theoretical and Computational Methods is responsible for the course.

Module where the course belongs to:

  • TCM300 Advanced Studies in Theoretical and Computational Methods

The course is available to students from other degree programmes.

  • Differential and integral calculus, linear algebra, complex numbers, (ordinary and partial) differential equations.
  • Elementary probability (either Todennäköisyyslaskenta I and/or II or similar knowledge, possibly from Fysiikan Matemaattiset Menetelmät IIa/b).
  • Courses in stochastics (Probability theory, Stochastic analysis etc.)
  • Courses in mathematical physics
  • You will learn to know the essential theories and methods of stochastics as well as stochastic models frequently encountered in applications.
  • You will understand how to treat mathematically random phenomena and related models.
  • If the implementation of the course emphasises more computational methods, you’ll learn to them also in practise in small tasks and/or a project work.

Can be taken in the early or later stages of studies. This can even be the only stochastics course you study.

Lectured every second year.

  • The course covers essential (theoretical and/or computational) methods in stochastics and emphasises their applications to natural sciences (and possibly also to other fields, e.g. finance and insurance mathematics). Although the topics may vary between years, we aim to cover the essential parts of background in the probability theory and topics in stochastic processes (e.g. Markov chains, random walks, Brownian motion, Poisson process) and stochastic calculus (integration with respect to random processes, Ito’s formula etc.).
  • The course is aimed to be self-contained for those students that are more interested in the applications. The course can be complementary to the other courses in stochastics (for those students that have studied or plan to study more stochastics courses) in that it emphasises more the applications.

Weekly lectures and exercises. Other teaching activities will be announced at the beginning of the course.

The course is graded based on the exam, exercises and the other compulsory course work announced at the beginning of the course.

Exam and exercises.