University of Oslo

This course gives an in-depth study in basic methods and practical tools for basal language technology (methods for automatic analyzation of language-based data). It covers both rule-based techniques, such as phrase structure grammar, and approximations with a starting point in machine learning, such as vector space semantics and classification. The course takes a look at some applications of methods for issues within language technology such as tagging, parsing, and text classification (such as sentiment analysis). The course has a strong practical component, with use of relevant tools and projects with written reports, among other things, which are required to qualify for the exam.

This course provides a basic introduction to machine learning (ML) and artificial intelligence (AI). With an algorithmic approach, it offers a practical understanding of the methods that are reviewed, not least through their own implementation of several of the methods. The course covers supervised classification based on, for example, artificial neural networks (deep learning), in addition to unsupervised learning (cluster analysis), regression, optimization (evolutionary algorithms and other search methods) and reinforcement learning, as well as design of experiments and evaluation. The course also provides an introduction to philosophical fundamental problems and ethical issues related to ML/AI, in addition to the history of the field.

This is an introductory course in English-language literature written by, about, or for gay men and lesbians in the twentieth century. It studies a variety of representations of homosexuality in a selection of novels, short stories, plays, and essays. The course also covers literature on other identities within the LGBTQ spectrum, such as bisexuality, asexuality, and transgender identities.

This course considers how scientists, journalists, and film makers communicate about climate change; what measures are used by activists, social media users, and "green influencers" to convey urgency and persuade others to engage; and how the challenges and solutions of the climate crisis can be visualized using stories, short videos, memes, news, infographics, and other media. It introduces people whose job it is to communicate about climate change and discuss issues such as trust, greenwashing, attention, engagement, mobilization, urgency, and apathy. The course is built on active participation: students collect and analyze a variety of climate change communication and team up with others to create a media product as part of their exam.

This is a higher level course (CEFR B2 - C1) for international students. The course is based on different types of non-fiction texts, fiction texts, radio and TV programs, and other types of written and oral presentations. Students learn to give oral presentations and to use language flexibly and appropriately for both social and academic purposes. Students are expected to contribute actively to discussions and debates, for example, by asking questions, justifying and arguing for their own opinions. Students are also expected to give feedback to each other. The learning objectives for written production in the curriculum Norwegian for immigrants - level C1 form the basis of the teaching, and the course is therefore useful for students who wish to take the Norwegian language test at level C1. This is a proficiency course with a final examination. 

This course provides an introduction to different methods for supervised learning (regression and classification). The course contains both model- and algorithm-based approaches. The main focus is supervised learning, but unsupervised methods like clustering are briefly discussed. The course also deals with issues connected to large amounts of data (i.e. "big data"). The course gives a good basis for further studies in statistics or data science, but is also useful for students who need to perform data analysis in other fields.