Ecolinguistics and frugal innovation
Table of Contents
What you will learn
At the end of the course, participants will be able to apply NLP for research or innovative projects, compare, explain and choose different methods, as well as question and test hypothesis. (Optional) Through practical use cases, participants will learn how to use Python to analyze data, visualize information and convey learnings with scikit-learn, NLTK, gensim or spacy to build simple proof of concepts and MVP.
Program overview
Course duration: 16 hours. 1h20 per week, for 12 weeks.
Level: Basic to advanced.
Topics: Computational linguistics, learning paradigms, models & limits, NLP.
(Recommended) Audience: Master students enrolled in a scientific field (e.g., data science, neuroscience, psychology), language learning and development practitioner (e.g., orthophoniste, teacher).
Course syllabus
Introduction
Motivate language studies.
Languages, vocabulary and alphabets
Give historical context.
Words, topics and sentences
Encode, decode information and meaning.
Keyword extraction
Combine analytical & synthetic skills.
Learning paradigms
Compare learning paradigms in NLP.
Generative vs discriminative learning
Create to understand.
1 - Debias language
Use language for social innovation.
2 - Carbon accounting
Use language for environmental protection.
3 - Fighting fake news
Identify fake news, counter hate speech.
Project presentations
Give and receive feedback.
FAQs
Are there prerequisites?
There are no prerequisites for the first course. A computer with Python installed and a Framagit account is required if you wish to experiment with the use cases. Statistics, maths and python libraries will be introduced along the course with practical use cases.
How often do the courses run?
Continuously, at your own pace. Some live webinars and cohorts will be scheduled to foster a dynamic learning environment and sense of community.
I followed CS224n at Stanford. Should I attend this course?
Yes! CS224n is essentially about deep learning which isn’t what this course is about. This course will give you new insights and ways to approach problems.
I worked in computational linguistics and designed simple solutions in the past. Could I share my learnings with you?
Yes of course! Feel free to reach out to chat and co-create the course. Thanks!