Course code MLA210

MLA210 Machine Learning applications in finance and technology

Norsk emneinformasjon

Search for other courses here

Showing course contents for the educational year 2022 - 2023 .

Course responsible: Ulf Geir Indahl
Teachers: Kristian Hovde Liland, Tor Kristian Stevik
ECTS credits: 10
Faculty: Faculty of Science and Technology
Teaching language: EN, NO
(NO=norsk, EN=Engelsk)
Teaching exam periods:
The course is implemented and censored each spring semester. 
Course frequency: Each spring semester.
First time: Study year 2021-2022
Course contents:
Matrix- and least-squares methods for pattern recognition and data analysis applications in technology and finance. Some applications are: Time series analysis, document analysis, portfolio optimization, process control and muliti-objective optimization. The programming language Julia will be used for implementation and computations.
Learning outcome:
The students will learn both the theoretical background and how to implement the methodology for analysing data of real world applications.
Learning activities:
The teaching will be given as lectures, practical exercises and project work..
Syllabus:
Will be announced in the beginning of the semester.
Prerequisites:
https://www.nmbu.no/course/math113

https://www.nmbu.no/course/math113MATH113/https://www.nmbu.no/course/math131131https://www.nmbu.no/course/math111MATH111/https://www.nmbu.no/course/math100100 og https://www.nmbu.no/course/inf120INF120 or similar courses in mathematics and programming.

Recommended prerequisites:
STAT100, DAT110 or a similar introduction course in statistics.

Mandatory activity:
Mandatory project exercises throughout the semester. Rules for approval of mandatory activity will be presented at the start of the semester.
Assessment:
Oral or written exam based on the syllabus and mandatory project exercises.
Nominal workload:
250 hours
Type of course:
4 hours lectures per week. 2 hours exercise groups per. week
Examiner:
The sensor will evauate the exam answers including the mandatory project exercises.
Allowed examination aids: A1 No calculator, no other aids
Examination details: Written exam: Letter grades