IKT721 - Statistical Signal Processing

This is an introductory course in statistical inference. The video below provides a description of the generality and extensive applicability of the contents that it covers. In addition, by completing this course, the student develops a solid foundation to understand the fundamentals of machine learning and artificial intelligence.

In line with the spirit of open education, all the lectures and material are available for everyone in this website.

Along with the aforementioned specific capabilities in estimation and hypothesis testing, the learning outcomes comprise the development of general skills involved in virtually any technical and scientific discipline, with emphasis on learning the research method. In particular, the course is articulated in such a way that the student learns the two-step procedure where 1) intuition is used as a tool to guide the researcher in which direction to move, and 2) the mathematical formalism is then used to rigorously establish the truth based on the insights from 1).

While many PhD courses teach research methods from a theoretical point of view, the approach here is learning by doing. PhD students eager to learn the research way of thinking while studying statistical inference are encouraged to enroll. Students wishing 5 "easy" ECTS credits may consider other alternatives, as this course involves attendance to the lectures, homework, and a project or exam.