Courses – Fakultet tehničkih nauka u Novom Sadu

Subject: Selected Chapters in Machine Learning (17.DRNI14)

Native organizations units: Sub-department for Applied Computer Science and Informatics

Type of studies	Title
Doctoral Academic Studies	Computing and Control Engineering (Year: 1, Semester: Summer)
Doctoral Academic Studies	Computing and Control Engineering (Year: 1, Semester: Summer)

General information:

Category	Scientific-professional
Scientific or art field	Applied Computer Science and Informatics
ECTS	10

The objective of the course is the acquisition of knowledge in the field of machine learning and understanding the possibilities of implementation of machine learning techniques and methods in different fields.

The student is able to develop new techniques and methods of machine learning and to implement the existing methods in different fields in a new and creative way.

Selected methods and techniques of machine learning. Selected problems whose solution requires the implementation of methods and techniques of machine learning. Examples of solved and unsolved problems. A part of the course work is conducted through independent individual research study work in the field of machine learning. The research study work requires the student`s active and constant interest in and reading of the primary scientific resources and, optionally, writing a paper in the field of machine learning.

Teaching methods include lectures, laboratory classes, homework assignments, and consultations. Lectures involve presenting the course materials using the necessary didactic tools while encouraging the students to participate actively. Laboratory classes (exercises) are realized through assignments that can be done independently or with the help of teaching assistants, as well as through homework assignments.

Authors	Title	Year	Publisher	Language
Bishop, C.M.	Pattern Recognition and Machine Learning	2006	Springer, New York	English
Goodfellow, I., Bengio, Y., Courville, A.	Deep Learning	2017	MIT Press, Cambridge	English
M. Magdon-Ismail, Y. AbuMostafa	Learning from Data	2012	AMLBook	English
S. Shalev-Schwartz, S. BenDavid	Understanding Machine Learning: From Theory to Algorithms	2014	Cambridge university press	English