Student Type: Tutkinto-opiskelija
Ohjelmoinnin alkeet 1–3 ECTS
Ohjelmoinnin alkeet on Oulun yliopiston tarjoama aloituskurssi. Kurssilla esitellään ohjelmoinnin peruskäsitteet sekä opetellaan perusteet Python-ohjelmointikielestä. Kurssille on jatkuva haku ja sen voi aloittaa milloin tahansa. Opiskelu perustuu tekstiin ja runsaisiin ohjelmointitehtäviin Python-kielellä. Kurssilla ei ole varsinaisia esitietovaatimuksia, mutta koska opiskelu on itsenäistä, on aiemmasta ohjelmoinnin tuntemuksesta hyötyä. Lopputyöstä on mahdollista saada suullinen palaute opettajalta. Kurssin sisältö
Artificial intelligence
Max amount of FITech students: 20 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. In this course, we aim to understand the basic mechanisms of Artificial Intelligence, so we focus on the fundamental principles. Artificial intelligence (AI) aims to understand thinking and intelligence
Software testing
Max amount of FITech students: 40 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. Course contents Learning outcomes After completing this course you Course material The course materials and exercises can be found on the course website: https://opencs.it.jyu.fi/software-testing/ Teaching schedule Schedule in the
Energy storage for sustainable buildings and districts
Sustainable energy transition requires integration of major technological changes in renewable energy production, energy storage for resilience and demand-side energy savings. The buildings sector is responsible for about one-third of global energy use and energy-related CO2 emissions. With the rising deployment of renewables, energy storage plays a critical role for shedding and shifting building loads
Wood products and processes
Max amount of FITech students: 200 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. The course presents the most relevant wood-based products, their production processes, properties and typical applications. Course contents This course presents the production processes and structures of widely used engineered
Forests, wood and carbon
Max amount of FITech students: 200 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. The course presents the role of wood and forests in the carbon cycle. Basic properties of wood material are covered, as well as processing from forest to different applications.
Applied mechanics of wood materials
Max amount of FITech students: 200 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. Course contents This course covers the basic principles of wood mechanics and the use of wood and wood-based products from the perspective of mechanical behavior. A fundamental overview of
Wood material science
Max amount of FITech students: 200 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. The course dives into the material science of wood, covering topics such as structure and anatomy, wood formation and wood and water interactions. Students will learn how the macroscopic
Software engineering with large language models
Familiarise yourself with the principles for training and fine-tuning large language models for software engineering tasks. Utilise large language models to assist in program development. Build applications that interact with large language models. Course contents Producing code with large language models, software engineering and software development life cycle, constructing programs with large language models, quality
Introduction to large language models
This is an introductory course to large language models and after completing the course the student will understand the key principles underlying the large language models and can also engineer prompts to improve output quality. No prior knowledge is needed to complete the course. Course contents Language models, large language models, prompting and prompt engineering,