Кто читает:: Школа лингвистики

Статус:: Курс обязательный

Когда читается:: 1-й курс, 3, 4 модуль

Преподаватели

Дроздова Ксения Андреевна

Клышинский Эдуард Станиславович

Full Syllabus

Abstract

The course is designed to further the students’ knowledge of natural language processing and to polish their programming skills. The course aims to provide the students with the programming and natural language processing knowledge and competencies necessary to plan and conduct research projects of their own leading to the M.Sc. dissertation and scientific publications.

Learning Objectives

The course aims: • to further the students’ programming skills; • to provide them with the necessary skills to write programs for experiments and corpus studies; • to teach them how to re-format data; • to teach them how to retrieve data from the Internet; • to teach the students how to write their code so that it is readable by other linguists; • to teach them how to present their research that involves coding in the written and in the oral form; • to provide an overview of some of the most exciting current computational projects; • to teach the students how to read and to assess critically linguistic research that uses computational methods; • to teach them how to formulate linguistic questions in a way that can be addressed computationally; • to teach them to conduct independent computational studies.

Expected Learning Outcomes

Students are able to conduct independent natural language processing studies.
Students are able to formulate linguistic questions in a way that can be addressed computationally.
Students are able to present their research that involves coding in the written and in the oral form.
Students are able to re-format data.
Students are able to read and to assess critically linguistic research that uses computational methods.
Students are able to retrieve data from the Internet.
Students are able to to write programs (code) for experiments and corpus studies.
Students are able to write their code so that it is readable by other linguists and programmers

Course Contents

Computer architecture I.
Data representation I.
Interfaces I.
Collaboration I.
Licensing.
Software design patterns.
Software creation I.
Software packaging I.
Collaboration II.
Computer architecture II.
Software creation II.
Data representation/Interfaces II.
Graphical and web interfaces.

Assessment Elements

homework 1
Students are required to submit two homework assignments; they are given a week to complete each assignment.
homework 2
In-class presentation
exam

Interim Assessment

2021/2022 4th module
0.25 * homework 2 + 0.25 * In-class presentation + 0.2 * homework 1 + 0.3 * exam

Bibliography

Recommended Core Bibliography

Perkins, J. Python Text Processing with NLTK 2.0 Cookbook: Use Python NLTK Suite of Libraries to Maximize Your Natural Language Processing Capabilities [Электронный ресурс] / Jacob Perkins; DB ebrary. – Birmingham: Packt Publishing Ltd, 2010. – 336 p.

Recommended Additional Bibliography

Sarkar, D. Text Analytics with Python: A Practical Real-World Approach to Gaining Actionable Insights from your Data [Электронный ресурс] / Dipanjan Sarkar; БД Books 24x7. – Chicago: Apress, 2016. – 412 p. – ISBN 978-1-4842-2387-1

Магистерская программа «Компьютерная лингвистика»

Introduction to Scientific Computing