The course introduces a selection of tools and formal methods applicable to diverse problems in computer science.

Lecture part introducing a set of selected topics, and student talks to stimulate discussions about individual formal topics (to acquire input and thoughts from fellow scientists).

Student talks about their own Ph.D-related topics complement the mix of contents, which includes (at least):Formal LogicComputational ComplexityTheory of Machine Learning

The final mark is based on the assessment of the talk, where the quality of presentation is measured in four dimensions:Talk content (depth)Slide designPresentation styleDuration of the talk (adherence to time limits)

Computational Learning Theory – An IntroductionComputational ComplexityLogic - An OverviewNonmonotonic Logic

Presentation