Micro-credential Machine Learning of Natural Language processing
AI and Data Science
AI and Data Science
Ignite your skills in artificial intelligence for language technology
Natural Language Processing is an integral component to applications of data science across the technological industry nowadays. Professionals in this domain, however, might struggle to keep up with the fast-paced developments in recent years. In particular the recent and impressive emergence of neural networks in machine learning as a go-to paradigm has rapidly altered the state of the art in artificial intelligence and challenges existing computational approaches to text.
This microcredential has been carved out as a balanced selection of contemporary modules from the MA in Digital Text Analysis that targets industry professionals who are interested in learning about modern machine learning and natural language processing. With an emphasis on project and team work, we develop practical applications on textual data, as well as solutions for the many issues that remain open in the field.
Professionals active in industry who wish to harness recent advances in AI and Deep Learning in the context of Natural Language Processing for Data Science.
Prospective students must have demonstrable programming skills in Python.
This micro-credential focuses on the following learning outcomes.
1. The participant will have theoretical knowledge about the history and the main frameworks of Machine Learning.
2. The participant will have theoretical knowledge of the main machine learning algorithms and paradigms and will study some of them in depth.
3. The participant will be able to develop machine learning pipelines and set up their own machine learning experiments using Python modules.
4. The participant will have theoretical and practical knowledge of machine learning using neural networks.
5. The participant will understand the fundamental problems and approaches in automatic Natural Language Processing and know its history as a subfield within Linguistics and Artificial Intelligence.
6. The participant will have insight into the basic algorithms developed within NLP for morphological, syntactic, semantic, and discourse processing.
7. The participant will acquire hands-on experience with software for text categorization, language understanding, translation, and generation.