URL study guide
https://tue.osiris-student.nl/onderwijscatalogus/extern/cursus?cursuscode=JBC090&collegejaar=2025&taal=enDescription
Language technology has long played an important, yet less overt role in society: language is used to query search engines, mobile devices often provide autocorrect and predictive writing, and automatic translation is often provided while browsing websites in other languages. Recent developments in chat-based text synthesis systems have brought natural language processing to the forefront of public attention, and claims of approaching human-level artificial intelligence run rampant. However, do models like ChatGPT actually understand language? How do models of language work, and how do they fail? What are the challenges in their learning tasks? How do we address the societal impact of these models?This course will equip students with the knowledge to consider and largely answer such questions. It takes a data-oriented approach to understanding developments at the intersection of language and AI, combining perspectives from computational linguistics, machine learning, and artificial intelligence. On completing the course, students will be able to judiciously apply natural language processing techniques in data science.
Objectives
- Explain pipelines and algorithms used to process natural language data.
- Implement NLP methods to analyze and transform natural language data.
- Evaluate the suitability of natural language data sources for a data science problem.
- Apply classical machine learning models and basic neural language models to language data.
- Explain the limitations of language processing techniques based on insights from Cognitive Science.