Monte Carlo methods
7.5 creditsMonte Carlo methods turn randomness into a computational tool. When a problem is too complex to be solved exactly, one can instead simulate many “possible worlds” and use the results to say something about what is expected to happen on average. In this course, you learn the probability-theoretic ideas that make these methods reliable, how to reformulate deterministic problems in probabilistic terms, and the core algorithms underlying simulation. You work with techniques for generating random variables from many types of distributions, simulating more complex stochastic models, and making simulations far more efficient through variance reduction (e.g., control variates, importance sampling, stratification, and Latin hypercube sampling). The course also introduces Metropolis–Hastings and Gibbs sampling in order to draw samples from complicated high-dimensional distributions.
Distance – study where you are
Distance learning can be structured in different ways – it may be entirely online, or include a few on-campus sessions or meetings at one of our learning centres. The common factor is that most of the learning happens online.
You communicate with your teacher and fellow students through a learning platform, which provides access to discussion forums, group work opportunities, and digital meetings. In many cases, you also have access to recorded lectures via the platform.
The advantage of distance learning is its flexibility – ideal for those who want more freedom to decide when and where to study. However, keep in mind that some mandatory elements of your programme may take place during working hours, even if they are conducted online.
Build your own degree
Did you know that you can combine single-subject courses to build your own degree? In this way, you can design your own degree based on your interests and the career you are aiming for. This does not apply to all courses so make sure to check with a study counsellor at the faculty. Learn more about how you can build your own degree and become unique on the labour market.