DIP414 Computer Aided Solution Processing

Code DIP414
Name Computer Aided Solution Processing
Status Compulsory/Courses of Limited Choice
Level and type Post-graduate Studies, Academic
Field of study Computer Science
Faculty
Academic staff Gints Jēkabsons, Jurijs Lavendels
Credit points 4.0 (6.0 ECTS)
Parts 1
Annotation In the lecture course, students learn elements of supervised machine learning and mathematical optimization with emphasis on regression methods and combinatorial optimization. The course also discusses methods for estimation of machine learning model's predictive performance, feature selection, optimization of model's structure, as well as practical applications of the methods..
Goals and objectives
of the course in terms
of competences and skills
The goal of the lecture course is for the students to gain knowledge on the principles of supervised machine learning, principles of regression, specific machine learning and optimization methods, evaluation of predictive models and optimization of their structure as well as to gain knowledge and skills in practical application of the covered methods.
Learning outcomes
and assessment
Understands the fundamental machine learning problems considered in the lecture course as well as understands how to solve them using specific methods. - Successfully answered tests and passed examination.
Is able to do own research on problems connected with the topics of the lecture course and develop own solutions as well as implement them in software. - Positively evaluated written report.
Is able to use methods and algorithms appropriate for the problems at hand. Is familiar with their operation and is able to apply them in practice. - Successfully completed individual assignments.
Course prerequisites Mathematics, Theory of probability and mathematical statistics

[Extended course information PDF]