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Topics in Theoretical Physics: Physics of Machine Learning


Admission Requirements


Description and Course Objectives

Topics in Theoretical Physics is a student seminar course. The purpose of the course is to gain familiarization with research methods. The first objective is to learn how to distill from a set of advanced review and current research articles a one hour lecture containing the essentials. The second objective is to present this material comprehensibly both in a lecture form as well as in a written summary. The course is built around a current physics research topic of interest. The topic for Spring 2018 will be The Physics of Machine Learning.


Physics Schedule

Mode of instruction

Students will be involved very actively. They both compose and present the lectures on advanced material on the topic of the course. This material will be provided by the instructor.

Assessment method

The student will be asked to present a topic in a well-prepared one-hour lecture. This preparation will be done in close collaboration/supervision of the lecturer mostly in the week before the presentation.

The student will also be asked to write a ± 5 page LaTeX summary of a presentation by one of your fellow students.

As a student seminar, the course is also interactive instead of simple lectures. The student is fully expected to ask questions frequently during and after the various presentations.

The final grade will be based on all three in the following proportion: – 30% Preparation – 40% Presentation – 30% Participation


Blackboard will be used to offer additional reading material and possible notifications about the course
To have access to Blackboard you need a ULCN-account.Blackboard UL

Reading list

Reading and other course material will be provided.


Koenraad Schalm
Oort 241