Natural Language Processing (Sommersemester 2022)
Dozent:
Prof. Dr. Gerard de Melo
(Artificial Intelligence and Intelligent Systems)
Website zum Kurs:
https://moodle.hpi.de/course/view.php?id=305
Allgemeine Information
- Semesterwochenstunden: 4
- ECTS: 6
- Benotet:
Ja
- Einschreibefrist: 01.04.2022 - 30.04.2022
- Prüfungszeitpunkt §9 (4) BAMA-O: 18.08.2022
- Lehrform: Vorlesung / Übung
- Belegungsart: Wahlpflichtmodul
- Lehrsprache: Englisch
- Maximale Teilnehmerzahl: 40
Studiengänge, Modulgruppen & Module
- BPET: Business Process & Enterprise Technologies
- HPI-BPET-K Konzepte und Methoden
- BPET: Business Process & Enterprise Technologies
- HPI-BPET-T Techniken und Werkzeuge
- BPET: Business Process & Enterprise Technologies
- HPI-BPET-S Spezialisierung
- OSIS: Operating Systems & Information Systems Technology
- HPI-OSIS-K Konzepte und Methoden
- OSIS: Operating Systems & Information Systems Technology
- HPI-OSIS-T Techniken und Werkzeuge
- OSIS: Operating Systems & Information Systems Technology
- HPI-OSIS-S Spezialisierung
- DATA: Data Analytics
- HPI-DATA-K Konzepte und Methoden
- DATA: Data Analytics
- HPI-DATA-T Techniken und Werkzeuge
- DATA: Data Analytics
- HPI-DATA-S Spezialisierung
- CODS: Complex Data Systems
- HPI-CODS-K Konzepte und Methoden
- CODS: Complex Data Systems
- HPI-CODS-T Techniken und Werkzeuge
- CODS: Complex Data Systems
- HPI-CODS-S Spezialisierung
- SECA: Security Analytics
- HPI-SECA-K Konzepte und Methoden
- SECA: Security Analytics
- HPI-SECA-T Techniken und Werkzeuge
- SECA: Security Analytics
- HPI-SECA-S Spezialisierung
- Digital Health
- HPI-DH-DS Data Science for Digital Health
- DICR: Digitalization of Clinical and Research Processes
- HPI-DICR-C Concepts and Methods
- DICR: Digitalization of Clinical and Research Processes
- HPI-DICR-T Technologies and Tools
- DICR: Digitalization of Clinical and Research Processes
- HPI-DICR-S Specialization
- APAD: Acquisition, Processing and Analysis of Health Data
- HPI-APAD-C Concepts and Methods
- APAD: Acquisition, Processing and Analysis of Health Data
- HPI-APAD-T Technologies and Tools
- APAD: Acquisition, Processing and Analysis of Health Data
- HPI-APAD-S Specialization
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 and information extraction to modern deep learning-based NLP using Transformers (e.g., BERT, GPT-3). It will cover recent techniques such as for explainable AI 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).
Lern- und Lehrformen
Lecture with integrated practical exercises.
This course will mostly take place in person. However, in the first 2 weeks, the lectures will be online on Zoom. Please join our Moodle instance for login details.
Non-HPI students can contact Sophie Bodien at office-deMelo(at)hpi.de to obtain access.
Leistungserfassung
60% Final Exam
40% Graded project-based assignments
In case of low participation, the exam can be replaced by an oral examination.
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