. "Artificial Intelligence"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "Applied deep learning"@en . . "2" . "The aim of this course is to provide an overview of modern applications of machine learning and develop practical skills in using deep neural networks for common machine learning tasks. The objective of this course is to provide an introduction into artificial neural network based models, as well as an introduction to existing API frameworks for training such models. Previous knowledge regarding machine learning is not expected. The practical assignments will be developed in Python programming language.\r\nThe language of instruction is Latvian.\r\nResults\tKnowledge: 1. Describe the main neural network machine learning approaches. (EQUANIE concepts E1-1, E-12) Skills: 2. Independently develop software systems with deep learning solutions. (EQUANIE realization E3-5, practice E5-1) Competencies: 3. Provide examples of suitable applications for machine learning methods and their limitations. (EQUANIE concepts E1-4, analysis E2-1)\r\n4. Evaluate practical problems which may require machine learning and propose the appropriate methods to solve them. (EQUANIE analysis E2-3, E2-4)" . . "Presential"@en . "FALSE" . . "Bachelor in Geoinformatics"@en . . "https://www.lu.lv/en/studies/study-process/courses/programme-search/?tx_lustudycatalogue_pi1%5Baction%5D=detail&tx_lustudycatalogue_pi1%5Bcontroller%5D=Course&tx_lustudycatalogue_pi1%5Bprogram%5D=21126&cHash=6f3dcba1688f6f3c1f0a12bd4f0d0313" . "243"^^ . "no data"@en . "KNOWLEDGE\r\n1. Understand the most important concepts and regularities in the field of natural sciences (natural and human geography, remote sensing, geodesy and cartography) and geoinformatics;\r\n2. Demonstrate typical basic and specialized knowledge in geoinformatics-related work fields, know geospatial data, standards and legal issues in the field of geoinformatics.\r\n\r\nSKILLS\r\n3. Perform professional activities in geoinformatics, independently obtain, formulate and analytically describe information, problems and solutions in geoinformatics, explain them and offer reasoned opinion in the discussion with both specialists and non-specialists;\r\n4. Critically analyse geoinformatic technologies, theories and problems;\r\n5. Demonstrate a scientific approach to problem solving, take responsibility and initiative in individual or team work, make decisions and find creative solutions in changing or uncertain circumstances.\r\n\r\nCOMPETENCE\r\n6. Independently obtain, select and analyse information and use it, make decisions and solve problems in geoinformatics, explain them and discuss them with specialists and non-specialists; develops solutions for the practical application of technology;\r\n7. Understand the problems and requirements of professional ethics in the field, assess the impact of their professional activity on the environment and society and participate in the development of the relevant professional field."@en . . "4"@en . "FALSE" . . . "Bachelor"@en . "Thesis" . "2800.00" . "Euro"@en . "3100" . "None" . "highly qualified geoinformatics specialists who are competitive in both the local and international labor market."@en . "no data" . "TRUE" . "Downstream"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .