Tutorials & Notebooks

Publicly available Jupyter notebooks for the Advanced Natural Language Processing (ANLP) and Agentic Conversational Search courses at Maastricht University. Hands-on tutorials covering neural NLP pipelines, transformer fine-tuning, retrieval-augmented generation, and agentic system design, with GPU-ready code and full working examples.

Course Tutorials

The tutorials below are hosted as public GitHub repositories. Clone the repo to work through the materials at your own pace, no sign-in required.

Agentic Conversational Search

IRTM, DACS, Maastricht University

Thirteen hands-on tutorials covering the full text-to-retrieval pipeline: from tokenisation and indexing to TF-IDF ranking, language models, neural retrieval, and systematic evaluation. All materials are implemented in Python and Jupyter Notebook.

Topics: Text preprocessing · Inverted indices · Ranking models · Evaluation metrics · Neural IR

Open on GitHub →

Advanced Natural Language Processing

ANLP, DACS, Maastricht University

Advanced NLP course covering modern transformer-based approaches: sequence modelling, fine-tuning pre-trained language models, RLHF, and applied NLP tasks. Predominantly Jupyter Notebook with GPU support via CUDA.

Topics: Transformers · Fine-tuning · RLHF · Sequence labelling · Applied NLP

Open on GitHub →