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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.

Studiju kurss rada padziļinātu izpratni par ķīmijas, ķīmijas tehnoloģijas un izvēlētas apakšnozares procesu aprakstīšanu ar matemātiskajiem modeļiem, algoritmizāciju un automatizāciju.  Studiju kursā izmantota augstas veiktspējas skaitļošanas platforma, lai studentim dotu piekļuvi virtuālajām mašīnām, kurās izvietoti zinātniskās programmēšanas rīki (Aspen, MatLab) studiju kursa uzdevumu risināšanai. Studiju kursā studējošie apgūst Eiropas iedzīvotāju digitālās kompetences ietvaram (DigComp) atbilstošās augstāko līmeņu digitālās prasmes.

This three-part short course introduces participants to the concepts and practical tools of production digitalization. The course provides hands-on experience with digital simulation, production performance evaluation, flexible systems design, and immersive VR technologies using the Visual Components software. Each module focuses on a key aspect of digital manufacturing and offers structured exercises in a simulated environment.

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The course provides an in-depth understanding of Robotic Process Automation (RPA), focusing on the design and use of RPA systems for structured business process automation. The course covers modern programming languages and management algorithms used in the development of RPA solutions. It examines methods and algorithms necessary for data management and process optimization, using intelligent system management methods. Theoretical exploration of programming libraries and development tools in the context of RPA is offered. The interaction of external input/output devices using system management and process automation methods is also discussed. The course analyzes data flow control methods. Through practical tasks, students are introduced to data processing methods, graph search algorithms, classification, optimization, machine learning, and big data processing methods, which are crucial for effective RPA implementation.

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The goal of this course is to study network management and control methods using Unix/Linux operating system environment.

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Take the first step toward mastering high-level digital skills!

This course is a component of the RTU study course "Vibrotechnology and Vibromachines" and is designed as a self-paced learning experience to provide an introductory insight into the subject and spark further interest. While the course is freely accessible, it does not offer a certificate of completion.

Learn how vibration problems are solved using numerical simulations, parallel programming, and high-performance computing.

This course combines theory with hands-on practice in ANSYS, Python, and JupyterLab, enabling learners to model and analyse vibrotechnical systems efficiently. Interactive content and flexible study formats support independent learning.