Course module NWI-NM048B Credits (ECTS) 6 Category MA (Master) Language of instruction English Offered by Radboud University; Faculty of Science; Wiskunde, Natuur- en Sterrenkunde; Lecturer(s) Coordinator prof. dr. H.J. Kappen Other course modules lecturer Examiner prof. dr. H.J. Kappen Other course modules lecturer Contactperson for the course prof. dr. H.J. Kappen Other course modules lecturer Lecturer prof. dr. H.J. Kappen Other course modules lecturer Lecturer dr. W.A.J.J. Wiegerinck Other course modules lecturer Academic year 2020 Period KW2-KW3   (02/11/2020 to 04/04/2021) Starting block KW2 Course mode full-time Remarks - Registration using OSIRIS Yes Course open to students from other faculties Yes Pre-registration No Waiting list No Placement procedure -

	Aims The aim of the course is to provide the student with a advanced concepts of modern machine learning at the international research level. The student will become familiar with the modern literature by presenting recent research papers on various topics. The student will implement these methods in computer code and apply them to real learning problems. See http://www.snn.ru.nl/~bertk/machinelearning/adv_ml.html for details. Content The course provides advanced topics in machine learning. The course is intended for Master's students in physics and mathematics. This course is the follow-up of the course Machine Learning, which is part of the Computational Data Science minor. The course provides a good preparation for a Masters' specialisation in Theoretical Neuroscience or Machine Learning. See http://www.snn.ru.nl/~bertk/machinelearning/adv_ml.html for details. Level Presumed foreknowledge The following courses are useful but not required: Voortgezette Kansrekening , Markov ketens, Toegepaste wiskunde 1 Test information Specifics Examination is weighted average of homework assignments and presentations.http://www.snn.ru.nl/~bertk/machinelearning
	Required materials Book David MacKay, Information Theory, Inference and Learning Algorithms, Cambridge University press. The entire book can be viewed on-screen at http://www.inference.phy.cam.ac.uk/mackay/itila/book.html Handouts Additional handouts and papers on the course website http://www.snn.ru.nl/~bertk/machinelearning/adv_ml.html Instructional modes Course occurrence Lecture Tutorial Tests Tentamen Test weight 1 Opportunities Block KW3, Block KW4