Zurück zur Auswahl
77575-01 - Seminar: Natural Language Processing (3 KP)
| Semester | Herbstsemester 2025 |
| Angebotsmuster | unregelmässig |
| Dozierende | Sepideh Alassi (sepideh.alassi@unibas.ch, BeurteilerIn) |
| Inhalt | Course Outline: Day 1: Text as Data: Anatomy of text, preprocessing pipelines, and the statistical properties of language. Day 2: Word Meaning and Representation: Word embeddings, semantic similarity, and co-occurrence matrices. Day 3: Language Structures: N-grams, POS tagging, dependency parsing, and Named Entity Recognition (NER). You will also learn how to train a custom NER model on your own corpus and evaluate its performance. Day 4: Higher Level Semantics: Sentiment analysis and topic modelling. Monday 15.12.2025 10:15-12:15 h and 14:15-16:15 h Tuesday 16.12.2025 10:15-12:15 h and 14:15-16:15 h Wednesday 17.12.2025 10:15-12:15 h and 14:15-16:15 h Thursday 18.12.2025 10:15-12:15 h and 14:15-16:15 h Venue will be announced |
| Lernziele | This course offers a practical introduction to Natural Language Processing (NLP) and demonstrates how its core concepts can be applied using Python. Each day is structured into two parts: morning sessions provide a theoretical overview of key topics, while afternoon sessions focus on practical examples and hands-on exercises. You will work with widely used Python libraries, including TensorFlow, spaCy, scikit-learn, Keras, and NLTK, to gain both conceptual understanding and practical skills. |
| Literatur | - Jacob Eisenstein, Introduction to Natural Language Processing, The MIT Press, 2019. - Hobson Lane, Hannes Hapke, Cole Howard, Natural Language Processing in Action: Understanding, Analyzing, and Generating Text with Python, Second Edition, Manning, 2025. |
| Bemerkungen | The course will be highly practical; therefore, attendance is mandatory. Please bring your own laptop with Python 3.12 installed. I also recommend installing the PyCharm IDE to facilitate programming. The Professional Edition is available free of charge for students—simply register with your UniBas email address on JetBrains. Download link: https://www.jetbrains.com/pycharm/download/ |
| Teilnahmevoraussetzungen | This course is intended for students with prior knowledge of Python, particularly those who have completed Introduction to Python for Humanities (course no. 64429-01). Students who have not taken this course but possess basic Python programming experience are encouraged to contact Dr. Sepideh Alassi to confirm that they meet the prerequisites. |
| Anmeldung zur Lehrveranstaltung | The number of participants is limited. In case of over-subscription, students of Digital Humanities will be given priority. |
| Unterrichtssprache | Englisch |
| Einsatz digitaler Medien | kein spezifischer Einsatz |
| Intervall | Wochentag | Zeit | Raum |
|---|
Keine Einzeltermine verfügbar, bitte informieren Sie sich direkt bei den Dozierenden.
| Module |
Modul: Creating, Analyzing and Visualizing of Data (Master Studienfach: Digital Humanities) |
| Prüfung | Lehrveranst.-begleitend |
| Hinweise zur Prüfung | At the end of the course, students will begin working on a mini-project to be submitted by mid-January 2026, accompanied by a written report. Assessment will be based on the quality of the project. |
| An-/Abmeldung zur Prüfung | Anmelden: Belegen; Abmelden: nicht erforderlich |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | Pass / Fail |
| Belegen bei Nichtbestehen | beliebig wiederholbar |
| Zuständige Fakultät | Philosophisch-Historische Fakultät, studadmin-philhist@unibas.ch |
| Anbietende Organisationseinheit | Digital Humanities Lab |