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These studies are available for the following degree students:</p><ul><li>Bachelor's Degree Programme in Mathematics</li><li>Master's Degree Programme in Mathematics</li><li>Bachelor's Degree Programme in Mathematics (Subject Teacher)</li><li>Master's Degree Programme in Mathematics&nbsp;(Subject Teacher)</li><li>Bachelor's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)</li><li>Master's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)</li><li>Doctoral Programme in Mathematics and Statistics</li><li>Doctoral Programme in Mathematics and Science (Specialication in Mathematics)</li><br></ul>","fi":"<p>Tämä opintojakso on tarjolla Matematiikan syventävät opinnot -ristiinopiskeluverkostossa. Verkoston opinnot ovat tarjolla seuraaville opiskelijoille:</p><ul><li>Matematiikan kandidaattiohjelma</li><li>Matematiikan maisteriohjelma</li><li>Matematiikan aineenopettajien kandidaattiohjelma</li><li>Matematiikan aineenopettajien maisteriohjelma</li><li>Matematiikan, kemian tai fysiikan aineenopettajan ja luokanopettajan kandidaattiohjelma (matematiikan opintosuunta)</li><li>Matematiikan, kemian tai fysiikan aineenopettajan ja luokanopettajan maisteriiohjelma (matematiikan opintosuunta)</li><li>Matematiikan ja tilastotieteen tohtoriohjelma</li><li>Matemaattisten tieteiden ja luonnontieteiden tohtoriohjelma (matematiikan opintosuunta)</li><br></ul>"},"cooperationNetwork":{"abbreviation":"matematiikansyventavat","name":{"en":"Cross-institutional studies in advanced courses in mathematics and statistics","fi":"Matematiikan ja tilastotieteen syventävien kurssien ristiinopiskelu","sv":"Korsstudier i fördjupade kurser i matematik och statistik"}}}],"gradeScaleId":"sis-0-5","outcomes":{"en":"After passing this course, the students will be able to describe the mathematical and algorithmics foundations of the machine learning approaches discussed in this course. They will also be able to implement machine learning models using the techniques discussed in the course, to train them, and use them for predictions.","fi":"Kurssin suoritettuaan opiskelija osaa kuvata tällä kurssilla käsiteltyjen koneoppimislähestymistapojen matemaattisia ja algoritmisia perusteita. Hän osaa myös toteuttaa koneoppimismalleja kurssilla käsitellyillä tekniikoilla, kouluttaa niitä ja käyttää niitä ennustamiseen."},"tweetText":null,"content":{"en":"The course builds on the Foundations of Machine Learning I and II courses and has them (or their content) as prerequisites. It focuses on combining multiple learners, on design and analysis of machine learning experiments, on kernel machines and graphical models. The courses combines the theory of machine learning with hands-on projects allowing the students to experiment with training various machine learning models on realistic datasets.","fi":"Kurssi rakentuu koneoppimisen perusteet I ja II -kursseille ja sisältää ne (tai niiden sisällöt) esitietoina. Se keskittyy useiden oppilaiden yhdistämiseen, koneoppimiskokeiden suunnitteluun ja analysointiin, ydinkoneisiin ja graafisiin malleihin. Kursseilla yhdistyvät koneoppimisen teoria käytännön projekteihin, jolloin opiskelijat voivat kokeilla erilaisten koneoppimismallien harjoittelua realistisilla tietojoukoilla."},"additional":{"en":"Lectures are not given every year but it&#39;s also possible to take the course independently. Academic year 2026-2026 available only for independent study.","fi":"Opintojaksoa ei luennoida säännöllisesti, mutta sen voi suorittaa myös itsenäisesti. Lukuvuonna 2026-2027 tarjolla vain itsenäisenä suorituksena."},"prerequisites":{"en":"MATE5427 Foundations of Machine Learning I\r\nMATE5428 Foundations of Machine Learning II","fi":"MATE5427 Foundations of Machine Learning I \r\nMATE5428 Foundations of Machine Learning II"},"compulsoryFormalPrerequisites":[],"recommendedFormalPrerequisites":[],"literature":[],"learningMaterial":null,"completionMethods":[]}],"prerequisiteCourseUnit":[],"prerequisiteModule":[]},"prerequisiteCourseUnitPage":{"nodes":[]},"prerequisiteModulePage":{"nodes":[]},"parentModulePage":{"nodes":[]}},"pageContext":{"type":"courseUnit","locale":"en","title":"Foundations of Machine Learning III","id":"otm-304d6d18-8b5a-38a4-b925-7f95643bfa0d","code":"MATE5439","prerequisiteCourseUnitIds":[],"prerequisiteModuleIds":[],"parentModuleIds":[],"curriculumPeriodStartDate":"2026-08-01","curriculumPeriodEndDate":"2027-08-01","coordinatingOrgIds":[],"searchable":false,"searchTags":null,"organisationIds":["otm-69f8ea31-de0c-3050-ab2a-e571fbab1f95"],"organisations":[],"attainmentLanguages":[],"hasSummerStudies":false,"teachingPeriods":[],"cooperationNetworkDirection":"INBOUND","hasCooperationNetworkSettings":true,"hasAvoinTeaching":false}}}