CONFERENCELU FACULTY OF EXACT SCIENCES AND TECHNOLOGY
Computer Science program:
Python Programming Language (DatZB084) - Bachelor
Lecturer: Assoc. Prof. Dr.sc.comp. U. Bojārs
Held: Tuesdays from 12:30 to 14:10.
The study course is taught in Latvian and English.
ECTS: 3 credit points
The aim of the course is to provide students with basic knowledge of the Python programming language.
Course tasks:
- acquire basic knowledge and programming skills in the Python programming language;
- improve the programming skills of the course participants;
- get acquainted with the available Python program packages and their use;
- acquire the main principles of solving problems using programming.
Applications of Language Technologies (DatZM037) - Master
Lecturer: Dr. sc. Comp. Normunds Grūzītis
Held: Thursdays from 16.30 to 18.00.
The aim of the course is to learn the latest language technologies for processing text and speech, including multimodal data, and to be able to use these technologies in the development of practical applications. The course will cover various types of transformer models for solving various types of tasks.
The main attention will be paid to multilingual models, their use, evaluation and adaptation options. Open source language models and programming frameworks will be used to acquire practical skills. The main methods and solutions for the combined use of generative language models and knowledge bases/graphs will also be covered.
FACULTY OF HUMANITIES OF THE UNIVERSITY OF LATVIA
Latvian Language, Literature and Culture Studies MSP:
Morphemics, Morphophonology and Database of Latvian Morphemes (ValoM119)
Lecturers: Dr.philol. Andra Kalnača and Ph.D. Kristīne Levāne-Petrova
Course language: Latvian
The aim of the study course is to provide knowledge about the morphemic structure and morphophonological phenomena of the language, their mutual connection and role in the creation of a morpheme database of the Latvian language in a general and at the same time practical aspect.
Study course tasks:
1) based on the facts of Latvian and other languages and their composition, to gain an understanding of morphemes, their types and regularities of association;
2) to learn and analyze the causes of morpheme variation, as well as the main principles of the interaction of morphology and phonology;
3) to develop linguistic competence in the creation and use of a morpheme database for research, using theoretical knowledge about the morphemics, morphophonology and regularities of the word formation system of the modern Latvian language.
Speech data processing and analysis (ValoM046)
Lecturers: Dr.philol. Ilze Auziņa and Mg.philol. Guna Rābante-Buša
Course language: Latvian and English
The aim of the course is to provide the knowledge and skills necessary for theoretical research and practical work in speech data processing and analysis, to introduce the basic concepts and methods of speech analysis, as well as the stages of speech corpus development.
The objectives of the course are
1) to provide knowledge about the acoustic and auditory properties of language sounds, speech data processing, analysis and visualization methods,
2) to introduce students to computer programs and tools suitable for acoustic analysis and multi-stage speech data annotation, and to promote their use in speech data research and analysis, as well as in the creation of speech corpora.
The study course strengthens knowledge about the various stages of the sound communication process, allows understanding the basic principles of speech technology.
Asian Studies BSP:
Introduction to Applied Linguistics and Language Technologies (ValoB077 - Bachelor)
Lecturers: Assoc. Professor, Dr. Philol. Jana Kuzmina, Assoc. Professor, Dr. Philol. Zigrīda Vinčela, Professor, Dr. Philol. Gunta Roziņa
Course language: Latvian and English
Course aim: to provide students with the opportunity to form and develop an understanding of applied linguistics and language technologies, to promote students' understanding of disciplines related to these fields and the concepts used in them, to acquire theoretical knowledge related to their application in practice.
The course emphasizes the development of text perception skills and content processing skills, skillfully using digital language technology tools for automatic analysis of text and speech. In addition, the course is oriented towards the systemic acquisition of knowledge necessary for students to be able to understand language use in appropriate contexts.
Course objectives: 1. to promote the synergy of applied linguistics and language technologies, creating students' understanding of the integrated acquisition of theoretical, practical and research skills, 2. to emphasize the application of acquired knowledge and developed skills in professional contexts, thus promoting the development of students' independent and critical thinking as well as the formation of analytical and research skills.
BSP of English, European Languages and Business Studies:
EU Institutional and Project Management Discourse (ValoB064)
Lecturers: Assoc. Professor, Dr. philol. Jana Kuzmina and Lecturer, Mg.philol. Margarita Spirida
Held: Thursdays at 10:30 - 14:00.
Language of instruction: English
The aim of the study course is to provide students with
The aim of the study course is to provide students with the opportunity to understand the EU institutional discourse, project management discourse, as well as to gain knowledge about document databases, text organization and analysis digital tools. The study course prepares students for the changing labor market situation and helps to develop digital competences, connect learning with practice and be proactive in their learning experience in the context of the EU institutional and project management discourse.
The objectives of the course are
1. to develop students' critical, interdisciplinary understanding of the EU as a multinational and multilingual union of states, providing insight into the development of the EU and its institutions;
2. to reveal the dynamic interaction of academic and professional discussions, how academic discussions on language policy and multilingualism resonate with practical terminology issues that arise in the process of information transfer in the EU context;
3. to develop students' understanding of discourse and genre theories that underlie the use of digital text analysis toolkits.
4. develop digital cross-disciplinary competence: instrumental skills in using digital tools for data extraction from databases, data visualization, text organization and analysis in institutional and professional contexts.
RIGA TECHNICAL UNIVERSITY
This semester, 6 study courses in English are available, which can be fully completed by anyone after registering on the mooc.rtu.lv portal!
Digital Edutainment Elements in Translation
The study course explores the possibilities offered by edutainment methods for various language technology-enabled applications in such fields as translation, localization, and creation of multi-lingual content, including educational game design and localization. The study course is envisioned for undergraduate students of study programs in humanities, interdisciplinary STEM+, and information technology.
Students will engage in a series of case studies, hands-on tasks, and lectures to explore the current offer of edutainment IT solutions, learn to select, use, and customize them for particular learning and industry needs, and solve the problems of limited definition advancing their digital competence and skills to Level 5–6 according to DIGICOMP 2.2 (digital game-based language learning, translation process coding, use and customization of immersive learning platforms, translation gaming).
Digital Semantics and Pragmatics
The study course is primarily aimed at developing high proficiency level competences and skills of the students mastering study programmes in different fields of humanities, social sciences, communication and human behavior sciences, interdisciplinary STEM+, and information technology. The study course is intended to provide a comprehensive overview of the fundamental issues associated with the retrieval, collection, organization, and processing of semantic and pragmatic data. The students will get acquainted with the state-of-the-art in the area of natural language processing (NLP) and natural language generation (NLG). Upon completion of the study course, you will be able to:
- actively participate in the work of various NLP technology development teams,
- conduct research in the field of digital semantics and pragmatics and solve a range of knowledge management tasks,
- co-create and/or create solutions to complex problems with limited definition that are related to modifying, refining, improving and integrating new content and information into the existing knowledge of digital semantics and pragmatics to create new and original ideas.
The study course is primarily aimed at developing advanced and highly specialized proficiency level competences and skills of the students mastering study programs in humanities, interdisciplinary STEM+ based, and information technology. The study course is envisioned for students with the basic knowledge of natural language processing (NLP) willing to advance their competence in sentiment analysis and textual data processing for a variety of applied industry-related tasks.
Machine Learning for Textual Data Processing
The study course offers undergraduate students the opportunity to develop their knowledge, competences, and skills in applying and customizing the available machine-learning tools for textual data processing to solve a range of practical industry-related and research tasks including but not limited to corpus and textual data analysis, data preprocessing and representation, sentiment analysis, and machine translation applications. Students shall develop a comprehensive understanding of the nature of the contemporary multi-modal digital text considering, inter alia ethical, security, and sustainability aspects of textual data collection, processing, and representation. They will gain experience in the practical application of data and text mining approaches, data structuring, and data visualization techniques, learn to validate, segment, and reuse the results of textual data analysis using corresponding machine-learning methods, and develop skills in using qualitative and quantitative data analysis techniques.
The study course ensures that students develop a comprehensive knowledge of machine translation (MT) systems and their operation algorithms, getting insights into the functionalities of neural MT tools and terminology management systems (TMS), addressing term retrieval issues, analysing machine translation quality and its determinants, performing source text pre- and post-editing, as well as developing critical and creative thinking skills for the application of machine translation solutions in cultural heritage preservation projects. Students will develop competences and skills in using translation and terminology management systems, elaborate their content creation and editing skills using relevant machine translation tools to streamline workflows in the creation of multi-lingual multimodal content.
The study course is primarily aimed at developing advanced and highly specialized proficiency level competences and skills of the students mastering study programmes in humanities, interdisciplinary STEM+ based, and information technology. The study course is intended to promote your awareness of various linguistic and non-linguistic semiotic systems and helps them develop a comprehensive understanding of the current trends in their change and development under the influence of digital technologies and media. Upon completion of the study course, you will:
- advance your knowledge of various sign systems, textual interactions, conceptual relations, spatial relations, sequential relations, and syntagmatic and paradigmatic dimensions of signification;
- develop advanced competence in creating and disseminating multimodal content via digital media;
- establish a sound competence for the development, customization, and maintenance of digital semiotic resources.