Department of Engineering
Dean:Dr. Ármann Gylfason
Email:ru@ru.is
Website:http://www.ru.is/tvd
TeachersView
MSc in Financial Engineering
Semesters:4
Years:2
ETCS:120
About majorFjármálaverkfræði er þverfagleg grein sem samþættir fjármálafræði við verkfræðilegar aðferðir, stærðfræðileg líkön, tölfræði, aðgerðagreiningu og hagnýta tölvunarfræði. Nám í fjármálaverkfræði hentar þeim sem hafa áhuga á t.d. áhættustýringu, afleiðuviðskiptum eða fjárstýringu. MSc námið er mótað að kröfum Verkfræðingafélags Íslands um fullnaðarmenntun í verkfræði.
Learning OutcomesView
Education cycle2
Legend
Mandatory course on majorTeaching language
Optional course on majorPrerequisites for course
Print
Vorönn/Spring 2024
More infoEnergy Financial AssessmentElectiveSE-833-FA2ECTS 6
More infoEngineering OptimizationElectiveT-423-ENOPECTS 6
More infoSleepElectiveT-424-SLEEECTS 6
More infoDecision Analysis for ManagementElectiveT-603-AKVAECTS 6
More infoInternship in Engineering IElectiveT-706-INT1ECTS 6
More infoInternship in Engineering IIElectiveT-706-INT2ECTS 6
More infoSystems BiologyElectiveT-765-SYBIECTS 8
More infoProject Management and Strategic PlanningElectiveT-803-VERKECTS 8
More infoDerivatives and risk managementCoreT-814-DERIECTS 8
More infoCreating a Complete Business Plan for a Technical Idea - Entrepreneurship and the Innovation ProcessElectiveT-814-INNOECTS 8
More infoModern Trends in Financial EngineeringElectiveT-816-MTFEECTS 8
More infoTissue Engineering and BiomaterialsElectiveT-828-TISSECTS 8
More infoGraduate Research Opportunities IElectiveT-829-GRO1ECTS 6
More infoFinite Element Analysis in EngineeringElectiveT-844-FEMMECTS 8
More infoNeural EngineeringElectiveT-863-NEURECTS 8
More infoWind PowerElectiveT-863-WINDECTS 8
More infoPower System OperationElectiveT-867-POSYECTS 8
More infoStability and Control in Electric Power SystemsElectiveT-867-STABECTS 8
More infoProtection Philosophy for Smart-GridsElectiveT-868-PROTECTS 8
More infoMSc ThesisCoreT-899-MEISECTS 30
More infoMSc ThesisElectiveT-900-MEISECTS 30
More infoMSc thesis IIElectiveT-901-MEI2ECTS 30
More infoBusiness Process ManagementElectiveV-716-BPMAECTS 7,5
More infoEntrepreneurial FinanceElectiveV-733-ENTRECTS 7,5
More infoBusiness Intelligence and AnalyticsElectiveV-784-REK5ECTS 7,5
More infoEntrepreneurship and Starting New VenturesElectiveX-204-STOFECTS 6
More infoExchange StudiesElectiveX-699-EXCHECTS 30
Sumar/Summer 2024
More infoGraduate Research Opportunities IElectiveT-829-GRO1ECTS 6
More infoExchange StudiesElectiveX-699-EXCHECTS 30
Haustönn/Fall 2024
More infoSpecial Topics in Energy IElectiveSE-801-STEECTS 1
More infoEnergy EconomicsElectiveSE-805-EC1ECTS 6
More infoSpecial Topics in Energy IIIElectiveSE-806-STEECTS 6
More infoEmbedded System ProgrammingElectiveT-738-EMBEECTS 8
More infoSimulation IIElectiveT-806-SIMUECTS 6
More infoQuality ManagementElectiveT-807-QUALECTS 6
More infoApplying Models in ManagementElectiveT-808-NOLIECTS 8
More infoData Mining and Machine LearningCoreT-809-DATAECTS 8
Year
1. yearPrint
SemesterFall 2024
Level of course4. Second cycle, introductory
Type of courseElective
PrerequisitesNo prerequisites.
ScheduleNo schedule found.
Lecturer
Jón Guðnason
Content
Pattern recognition system, classifier design cycle and learning. Statistical pattern recognition, Bayesian decision theory, maximum likelihood and Bayesian parameter estimation. Linear models for classification. Principal component analysis. Multilayer neural networks. Nonparametric methods: k-nearest neighbours and Parzen kernels. Kernel methods and support vector machines. Unsupervised classification, K-means clustering, Gaussian mixture models and expectation maximization. Combination of classifiers, bagging and boosting.
Learning outcome - Objectives
After the course the students should be able to recall, describe and define, the following terms:Pattern recognition system, classifier design cycle and learning. Statistical pattern recognition, Bayesian decision theory, maximum likelihood and Bayesian parameter estimation. Linear models for classification. Principal component analysis. Multilayer neural networks. Nonparametric methods: k-nearest neighbours and Parzen kernels. Kernel methods and support vector machines. Unsupervised classification, K-means clustering, Gaussian mixture models and expectation maximization. Combination of classifiers, bagging and boosting.After the course the students should be able to apply the data mining methods and implement the machine learning algorithms presented in the course using standard programming languages such as Python or Matlab and software packages such as scikit-learn andWeka.After the course the students should be able to design a suitable machine learning algorithm for a real world problem, evaluate its performance, compare different designs and implementations and interpret the results. The students should also be able to present findings and new results in the subject.
Course assessment

Reading material
No reading material found.
Teaching and learning activities

Language of instructionEnglish
More infoOptimization MethodsCoreT-810-OPTIECTS 8
More infoApplied ProbabilityCoreT-811-PROBECTS 8
More infoFinancial Engineering of the FirmCoreT-814-FINAECTS 8
More infoManaging Research and Development - Methods and ModelsElectiveT-814-PRODECTS 8
More infoFixed Income and Interest Rate ModellingCoreT-815-FIXEECTS 8
More infoAdvanced Biomechanics IIElectiveT-828-BIOMECTS 8
More infoEnergy in Industrial ProcessesElectiveT-863-EIIPECTS 8
More infoNumerical fluid flow and heat transferElectiveT-864-NUFFECTS 8
More infoPrecision Machine DesignElectiveT-865-MADEECTS 8
More infoHigh Voltage EngineeringElectiveT-866-HIVOECTS 8
More infoSmart-Grid and Sustainable Power SystemsElectiveT-867-GRIDECTS 8
More infoComputer Vision ApplicationsElectiveT-869-COMPECTS 6
More infoMSc ThesisCoreT-899-MEISECTS 30
More infoMSc ThesisElectiveT-900-MEISECTS 30
More infoMSc thesis IIElectiveT-901-MEI2ECTS 30
More infoExchange StudiesElectiveX-699-EXCHECTS 30
Vorönn/Spring 2025
More infoSleepElectiveT-424-SLEEECTS 6
More infoDecision Analysis for ManagementElectiveT-603-AKVAECTS 6
More infoInternship in Engineering IElectiveT-706-INT1ECTS 6
More infoInternship in Engineering IIElectiveT-706-INT2ECTS 6
More infoRobust and Adaptive Control, with Aerospace ApplicationElectiveT-738-CONTECTS 8
More infoProject Management and Strategic PlanningElectiveT-803-VERKECTS 8
More infoDerivatives and risk managementCoreT-814-DERIECTS 8
More infoCreating a Complete Business Plan for a Technical Idea - Entrepreneurship and the Innovation ProcessElectiveT-814-INNOECTS 8
More infoModern Trends in Financial EngineeringElectiveT-816-MTFEECTS 8
More infoTissue Engineering and BiomaterialsElectiveT-828-TISSECTS 8
More infoFinite Element Analysis in EngineeringElectiveT-844-FEMMECTS 8
More infoNeural EngineeringElectiveT-863-NEURECTS 8
More infoWind PowerElectiveT-863-WINDECTS 8
More infoPower System OperationElectiveT-867-POSYECTS 8
More infoStability and Control in Electric Power SystemsElectiveT-867-STABECTS 8
More infoMSc ThesisCoreT-899-MEISECTS 30
More infoMSc ThesisElectiveT-900-MEISECTS 30
More infoMSc thesis IIElectiveT-901-MEI2ECTS 30