Hasso-Plattner-InstitutSDG am HPI
Hasso-Plattner-InstitutDSG am HPI
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Natural Language Processing (Sommersemester 2023)

Dozent: Prof. Dr. Gerard de Melo (Artificial Intelligence and Intelligent Systems)
Website zum Kurs: https://moodle.hpi.de/course/view.php?id=416

Allgemeine Information

  • Semesterwochenstunden: 4
  • ECTS: 6
  • Benotet: Ja
  • Einschreibefrist: 01.04.2023 - 07.05.2023
  • Prüfungszeitpunkt §9 (4) BAMA-O: 17.08.2023
  • Lehrform: Vorlesung / Übung
  • Belegungsart: Wahlpflichtmodul
  • Lehrsprache: Englisch
  • Maximale Teilnehmerzahl: 40

Studiengänge, Modulgruppen & Module

IT-Systems Engineering MA
  • IT-Systems Engineering
    • HPI-ITSE-E Entwurf
  • IT-Systems Engineering
    • HPI-ITSE-K Konstruktion
  • BPET: Business Process & Enterprise Technologies
    • HPI-BPET-K Konzepte und Methoden
  • BPET: Business Process & Enterprise Technologies
    • HPI-BPET-T Techniken und Werkzeuge
Data Engineering MA
Cybersecurity MA
Digital Health MA
Software Systems Engineering MA

Beschreibung

This course covers a broad range of topics relating to natural language processing (NLP) and computational linguistics, ranging from traditional linguistically oriented tasks such as syntactic parsing to modern deep learning-based NLP using Transformers (e.g., BERT, GPT-3, ChatGPT). It will cover recent techniques such as for prompt optimization and data augmentation, as well as applications such as conversational agents, machine translation, and sentiment analysis.

Voraussetzungen

This course requires solid programming skills as well as high school-level mathematics (especially basic linear algebra and probability theory).

Some prior familiarity with machine learning is recommended. Prior familiarity with deep learning is helpful, but not required.
 

Lern- und Lehrformen

Lectures with some integrated tutorial sessions

Leistungserfassung

The grade is based exclusively on a written exam.

As a precondition to being able to take the exam, students are required to complete a series of homework assignments to a sufficient degree (50% of points on each).

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