ONLINE LEARNING PLATFORM

Pamatkurss topošajiem būvinženieriem, lai tālāk apgūtu RTU studiju kursu “Būvdarbu tehnoloģija un darba drošība”

Learn what Artificial Intelligence (AI) is by understanding its applications and key concepts including search, knowledge representation and machine learning.

Lietišķās komunikācijas ar atsevišķām personām, personu grupām un institūcijām pamatprincipi

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).

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 course is aimed at students majoring in technical translation, researchers, academic staff, etc.

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.

This short course provides participants with a practical and applied overview of industrial robotics in manufacturing. Over three sessions, the course covers the fundamentals of robot-based workplace design, the implementation of robotic operations (e.g., pick-and-place and grinding), and the use of ABB RobotStudio for virtual simulation and programming. Participants will gain hands-on experience in configuring robot work cells, programming robot movements, and optimizing robotic processes in a simulated environment.