{"id":null,"code":"TKO_7106","name":{"valueFi":"Probabilistic Programming","valueEn":"Probabilistic Programming","valueSv":"Probabilistic Programming"},"credits":5.0,"minCredits":5,"maxCredits":5,"tags":[],"createdAt":1790534323103,"contentList":[{"title":{"valueFi":"Osaamistavoitteet","valueEn":"Learning outcomes","valueSv":""},"content":{"valueFi":"This advanced course provides an overview into statistical and probabilistic programming in modern AI & data science.\r\n\r\nAfter taking the course the student will\r\n- understand the basics of probabilistic data analysis\r\n- know how this framework can be applied in practice using the tools of probabilistic programming\r\n- is able to construct a complete reproducible statistical data analysis workflow","valueEn":"This advanced course provides an overview into statistical and probabilistic programming in modern AI & data science.\r\n\r\nAfter taking the course the student will\r\n- understand the basics of probabilistic data analysis\r\n- know how this framework can be applied in practice using the tools of probabilistic programming\r\n- is able to construct a complete reproducible statistical data analysis workflow","valueSv":"This advanced course provides an overview into statistical and probabilistic programming in modern AI & data science.\r\n\r\nAfter taking the course the student will\r\n- understand the basics of probabilistic data analysis\r\n- know how this framework can be applied in practice using the tools of probabilistic programming\r\n- is able to construct a complete reproducible statistical data analysis workflow"}},{"title":{"valueFi":"Sisältö","valueEn":"Content","valueSv":""},"content":{"valueFi":"Main contents:\r\n- Statistical workflow design\r\n- Basics of probabilistic data analysis\r\n- Introduction to probabilistic programming","valueEn":"Main contents:\r\n- Statistical workflow design\r\n- Basics of probabilistic data analysis\r\n- Introduction to probabilistic programming","valueSv":"Main contents:\r\n- Statistical workflow design\r\n- Basics of probabilistic data analysis\r\n- Introduction to probabilistic programming"}},{"title":{"valueFi":"Suoritustavat","valueEn":"Study methods","valueSv":""},"content":{"valueFi":"Active participation + exercises + course assignment\r\n\r\n- Lectures (8 x 2h)\r\n- Exercise session (8 x 2h)\r\n- Weekly reading assignment (8 x 6h)\r\n- Weekly programming assignment (7 x 4h)\r\n- Writing and finalizing independent course assignment (27 h)\r\n\r\nTotal: 135 hours (5 ECTS)","valueEn":"Active participation + exercises + course assignment\r\n\r\n- Lectures (8 x 2h)\r\n- Exercise session (8 x 2h)\r\n- Weekly reading assignment (8 x 6h)\r\n- Weekly programming assignment (7 x 4h)\r\n- Writing and finalizing independent course assignment (27 h)\r\n\r\nTotal: 135 hours (5 ECTS)","valueSv":""}},{"title":{"valueFi":"Toteutustavat","valueEn":"Course unit methods","valueSv":""},"content":{"valueFi":"- Lectures\r\n- Independent assignments\r\n- Exercise/demonstration sessions","valueEn":"- Lectures\r\n- Independent assignments\r\n- Exercise/demonstration sessions","valueSv":""}},{"title":{"valueFi":"Oppimateriaalit","valueEn":"Learning material","valueSv":""},"content":{"valueFi":"- Bayesian Data Analysis (3rd edition), A. Gelman et al. (2022)\r\n\r\n- Additional supporting materials include lecture slides, code examples, and assignments.\r\n\r\n- Probabilistic programming exercises are implemented in Stan.\r\n\r\n- Participants have the flexibility to choose the language for exercises and assignments. Example solutions will be provided in R, which is also the recommended language.","valueEn":"- Bayesian Data Analysis (3rd edition), A. Gelman et al. (2022)\r\n- Additional supporting materials include lecture slides, code examples, and assignments.\r\n- Probabilistic programming exercises are implemented in Stan.\r\n- Participants have the flexibility to choose the language for exercises and assignments. Example solutions will be provided in R, which is also the recommended language.","valueSv":""}},{"title":{"valueFi":"Lisätiedot","valueEn":"Further information","valueSv":""},"content":{"valueFi":"- Course will be held in English (except if all participants are Finnish speaking, the language can be agreed during the first lecture)\r\n- Registration in Peppi","valueEn":"- Course will be held in English (except if all participants are Finnish speaking, the language can be agreed during the first lecture)\r\n- Registration in Peppi","valueSv":""}},{"title":{"valueFi":"Kurssikirjallisuus","valueEn":"Literature","valueSv":""},"content":{"valueFi":"1.  ","valueEn":"1.  ","valueSv":"1.  "}},{"title":{"valueFi":"Esitietovaatimukset","valueEn":"Qualifications","valueSv":""},"content":{"valueFi":"This is an advanced course in statistical data analysis.\r\n\r\nThe participants are expected to have:\r\n- programming experience (preferably R, Julia, or Python)\r\n- solid background knowledge of statistics, data analysis and machine learning\r\n\r\nCourses on statistical data analysis, knowledge discovery, Bayesian analysis are recommended prerequisites but not formally required.","valueEn":"This is an advanced course in statistical data analysis.\r\n\r\nThe participants are expected to have:\r\n- programming experience (preferably R, Julia, or Python)\r\n- solid background knowledge of statistics, data analysis and machine learning\r\n\r\nCourses on statistical data analysis, knowledge discovery, Bayesian analysis are recommended prerequisites but not formally required.","valueSv":""}},{"title":{"valueFi":"Arviointiasteikko","valueEn":"Assessment scale","valueSv":""},"content":{"valueFi":"0-5","valueEn":"0-5","valueSv":"0-5"}},{"title":{"valueFi":"Arviointikriteerit","valueEn":"Assessment criteria","valueSv":""},"content":{"valueFi":"Weekly assignments, independent course assignment","valueEn":"Weekly assignments, independent course assignment","valueSv":""}},{"title":{"valueFi":"Arviointikriteerit 2","valueEn":"Assessment criteria 2","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}},{"title":{"valueFi":"Arviointikriteerit 3","valueEn":"Assessment criteria 3","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}},{"title":{"valueFi":"Arviointikriteerit 4","valueEn":"Assessment criteria 4","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}},{"title":{"valueFi":"Kielet","valueEn":"Languages","valueSv":""},"content":{"valueFi":"englanti","valueEn":"English","valueSv":"engelska"}},{"title":{"valueFi":"Taso","valueEn":"Level","valueSv":""},"content":{"valueFi":"Syventävät opinnot","valueEn":"Advanced Studies","valueSv":""}},{"title":{"valueFi":"Oppiaine","valueEn":"Subject","valueSv":""},"content":{"valueFi":"Tietojenkäsittelytieteet","valueEn":"Computer Science","valueSv":"Computer Science"}},{"title":{"valueFi":"Vastuuhenkilöt","valueEn":"Person in charge","valueSv":""},"content":{"valueFi":"Ville Laitinen, Leo Lahti","valueEn":"Ville Laitinen, Leo Lahti","valueSv":"Ville Laitinen, Leo Lahti"}},{"title":{"valueFi":"Luokittelu","valueEn":"Classification","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}},{"title":{"valueFi":"Linkit","valueEn":"Links","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}}]}