Lund University

The course is an introduction to manufacturing processes, ranging from machining operations to production quality control and production cost analysis, according to requirements of the Smart Manufacturing. The course provides an overview of systems and methods to monitor the machining operations and control the production quality by in- and post-process measurements. Part of the course is focused on introduction to the development of data acquisition and monitoring systems based on Artificial Intelligence (AI) and Machine Learning (ML) techniques and their implementation in manufacturing processes in academy and industry environments. The course is given as lectures with computer exercises and laboratory sessions and a task to train the student to elaborate on the material presented in the lectures. A project gives the student an opportunity to independently solve a problem for automatized process monitoring and production control. Assumed prior knowledge: MMT012/MMTF20 Production and Manufacturing Methods or MMTA05 Production Systems or MMTF01 Production and FKM015/FKMA01 Materials Engineering, Basic Course.
 

The course covers methods for data mining and business analytics and their usage in making strategic business decisions. It concentrates on the modelling aspects of data mining and provides tools for better understanding key methods of data exploration, visualization, classification, prediction, and clustering. The course starts with data visualization and getting to know features hidden in the data. Traditional regression models and hypothesis testing are practiced using real data. This introduction to traditional approaches then leads to the discussion of more advanced methods such as, discriminant analysis, classification and clustering methods, which are useful in finding patterns hidden in the data. The course deals with various types of data such as categorical data, time series, text data, and network data, among others. The fundamentals of building suitable models are discussed. Illustrations are carried out using the statistical package R. 

 

The course extends the student's Swedish vocabulary and ability to adapt their Swedish to different communication situations and to provide an opportunity to develop the ability to express themselves in a grammatically correct and varied manner. In addition to the skills training, the course also covers the typical features of Swedish grammar and phonetics. Written proficiency is practiced through written assignments of various kinds as well as summaries and presentations based on texts they have read or listened to an active vocabulary is built up through the reading of primarily newspaper articles and contemporary Swedish literature. Current societal issues are discussed and summarized. The pronunciation exercises have a particular focus on phonemic quality and prosody. To be admitted to the course, students must meet the general entry requirements for higher education in Sweden (with the exception of proficiency in Swedish) and have knowledge equivalent to SVEH15 Swedish for Students with a Foreign Background: Level 5, 7.5 credits

The purpose of the course is that the students should learn how to write efficient programs in the C language. In order to achieve this main purpose, three other purposes of the course are that the students should learn about (1) the ISO C18 language, (2) modern computer architecture, from the perspective of the programmer, with focus on microprocessors and cache memories, and (3) modern tools to evaluate C programs in terms of correctness and efficiency.

The course takes an interdisciplinary perspective and approach and is jointly conducted by the Department of Psychology and the Lund University Centre for Sustainability Studies (LUCSUS). It is aimed at those who wish to learn about the complex linkages between psychology, climate change, and sustainability, and apply them in their respective fields of work or study. Explore the ways our changing climate affect individuals and groups, including climate distress and its consequences, the psychological and behavioral factors that can drive the climate crises, and the theories and practices that can support skillful action across individual, collective and system levels. The course draws upon research from several fields, such as evolutionary, cognitive, social, industrial/organizational, and clinical psychology, behavioral economics, and sustainability science. The course includes experiential learning and practices drawing from evidence-based psychological methods (e.g., journaling, listening and communication exercises, values reflections), contemplative methods such as meditations and mindfulness, and nature explorations. The course is taught in English and includes both on-site and online education.

The course takes its starting point in the recurrent discussion on how to manage risks and build security to avoid crises in organizations. The course provides the tools to understand risk management, taking into account perspectives from the social sciences, business administration, and the humanities.

This course covers the theoretical foundations of the standard model of particle physics and its possible extensions. Among topics covered are the building blocks of the standard model, strong and electroweak interactions, CP violation, neutrino oscillations, and grand unification and supersymmetry.