- Nexus Linguarum
- DGN_linkeddata-advanced
- Starts:
- The Linguistic Linked Data field studies techniques and tools aimed at modelling and publishing language resources on the Web, in ways that enable their data interoperation and reuse. During this course you will be introduced to some advanced topics on linguistic linked data as well as its application to some fields like lexicography or terminology, among other aspects. This course is the continuation of another one that covers the essentials of linguistic linked data (Linguistic Linked Data – Essentials) that we encourage you to take in preparation for this one.
Featured Courses
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- Nexus Linguarum
- DGN_linkeddata-essentials
- Starts:
- The Linguistic Linked Data field studies techniques and tools aimed at modelling and publishing language resources on the Web, in ways that enable their data interoperation and reuse. During this course you will acquire the fundamental notions around linguistic linked data and will also gain practical experience on its main tools and techniques. This first course covers the essentials of linguistic linked data and has a continuation (Linguistic Linked Data – Advanced Topics) that we encourage you to take in order to acquire a complete picture of the field.
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- German UDS
- DGN_introduction-ai
- Starts:
- This course provides an overview of the field of Artificial Intelligence. In recent years, AI has become a core technology for many types of applications. While the original intention of the pioneers was to understand how humans solve problems and how cognition works, AI has diversified. Today, we have three main types of AI: traditional or symbolic AI uses logic and combinatorics to find solutions to optimization problems. Subsymbolic AI is related to neural networks. Here, problems are encoded in such a way that large networks process the data through many layers of processing until a solution is found. Probabilistic AI deals with knowledge graphs and the calculation of probabilities over them. In the course, we will give examples of each type of AI application. We will also discuss the ethical problems associated with AI systems, liability issues, and future applications.
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