Descriptive sheet of the TU MET-NLPF

TU MET-NLPF - Fundamentals of natural language processing
Objective Understanding the main natural language processing (NLP) approaches used to analyze textual data. Provide the students with methodologies and tools to experiment NLP usage for public health purposes.
Knowledge to be acquired
  • The role of NLP in public health
  • The main principles of NLP approaches
  • Strengths and weaknesses of different NLP approaches
Skills to be acquired
  • Understanding how textual information could be exploited for public health purposes
  • Being able to carry out basic NLP analyses
Description
  • Applications and interests of NLP in Public Health
  • Basic concepts and definitions (lexicon, morphology, syntax, semantics; corpus, word segmentation, n-grams, lemmatization, morphosyntactic labeling...)
  • Brief history; different types of approaches: human knowledge-based (lexicons, rules), machine learning (statistical learning, representation learning, deep learning)
  • Manual annotation of corpus
  • Principle and interest of pattern-matching, regular expressions
  • Principle and interest of dictionary and ontology approaches for annotation
  • Principle and interest of ML & Deep Learning approaches - embedding, recurrent network, attention-based model
  • Real world examples
Pedagogical method Courses on-line by NetConference, distance mentoring over the Internet.
Pre-requisite Knowledge of computer use, computer communication and presentation tools.
Total hours Around 23 hours per NetConference + personal work.
ECTS 2
Place Faculté des sciences médicales et paramédicale de Marseille
Dates See the schedule for this TU 
Head Jean-Charles DUFOUR
Teachers Jean-Charles DUFOUR, Julien GROSJEAN, Antoine NEURAZ, Aurélie NEVEOL, Bastien RANCE, Pierre ZWEIGENBAUM
TU – mandatory

This TU is mandatory for the Master 2 of Public Health:

  • AI4PH: Artificial Intelligence for Public Health
TU – optional  
Assessment of knowledge

A single examination is organised, in accordance with the Aix Marseille University rule.

For this single session, the assessment of knowledge of this teaching unit is based on:

  • Continuous assessment of knowledge with various homework assignments, tests and exercises. This continuous assessment will have a coefficient of 1 in the final mark.
  • An oral examination. This exam will have a coefficient of 4 in the final grade. A personal convocation will be sent by e-mail to each student.

To validate a UE, it is necessary to obtain a mark ≥ 10.
Educational resources All course materials will be available on the teaching on-line platform AMeTICE.