Основы программирования

Магистратура 2021/2022

Статус: Курс адаптационный (Лингвистическая теория и описание языка)

Направление: 45.04.03. Фундаментальная и прикладная лингвистика

Кто читает: Школа лингвистики

Где читается: Факультет гуманитарных наук

Когда читается: 1-й курс, 1 модуль

Формат изучения: без онлайн-курса

Охват аудитории: для всех кампусов НИУ ВШЭ

Преподаватели: Попова Дарья Павловна

Прогр. обучения: Лингвистическая теория и описание языка

Язык: английский

Кредиты: 3

Контактные часы: 32

Full Syllabus

Abstract

For the R version (in 2022/23 it will be R): The course is an introduction to R. It aims to familiarize students with the basics of R programming: data types, functions, packages for text processing, data formatting, visualization. For the Python version: The course is an introduction to data processing and programming for theoretical linguists. It assumes little to no background in programming. The course aims to make the students comfortable with programming and with using programming in their own linguistic research. The first goal of the course is to introduce the basics of programming; the second goal of the course is to show the students that they can solve linguistic problems that they are interested in and working on using the tools they were given. The course provides an opportunity for the students to work on their own research problem as their final project.

Learning Objectives

to teach students the basics of R/Python (for 2022/23, it will be R);
to make students comfortable using programming in their linguistic research;
to familiarize them with some of the advances in data processing and natural language processing;
to teach them how to create a linguistic corpus, how to retrieve data from the Internet, how to parse it, how to analyze it computationally;
to teach students how to present their computational work;
to teach students how to read each others’ code and how to ethically use open access code written by somebody else.

Expected Learning Outcomes

For the R version: students will be able to use different R packages. For the Python version: students will be able to write simple scripts in Python in order to use them in their own linguistic research;
For the R version: students will be able to work with complex data types. For the Python version: students will be able to use regular expressions for information extraction;
For the R version: students will be able to write loops and statements. For the Python version: students will be able to retrieve data from the Internet, parse it and use it for linguistic processing;
For the R version: students will be comfortable using R, they will learn about functions, variables, data types. For the python version: students will be comfortable with the Unix shell and simple commands related to processing text
For the R version: students will learn how to import and export data. For the Python version: students will know basic constructions and functions of Python, as well as the most frequently used functions and modules used for text processing;
For the R version: students will learn to write their own functions, to retrieve data from the Internet. For the Python version: students will learn how to retrieve data from the Internet
students will learn how to structure their code, how to make it readable and reusable, and how to present it to other linguists.
students will learn to present computational research

Course Contents

For the R version of the course: Interacting with R. Functions. Variables. Logical operators. For the python version of the course: Interacting with Python. Code presentation.Datatypes and variables
For the R version of the course: tidyverse. For the Python version: Control structures
For the R version: complex data types. For the Python version: Input and output. Modules
For the R version: if and for statements. For the Python version: Regular expressions
For the R version: using different R packages. For the Python version: Text manipulation. Choosing a final project
For the R version: writing functions, internet data. For the Python version: Internet data
Visualization. Final project consultation
Final project presentations

Assessment Elements

Homework assignment 1 (written format)
Homework assignment 2 (written format)
Homework assignment 3 (written format)
Final project (written format)

Interim Assessment

2021/2022 1st module
0.2 * Homework assignment 3 (written format) + 0.2 * Homework assignment 1 (written format) + 0.4 * Final project (written format) + 0.2 * Homework assignment 2 (written format)

Bibliography

Recommended Core Bibliography

Gries, S. T. (2013). Statistics for Linguistics with R : A Practical Introduction (Vol. 2nd revised edition). Berlin: De Gruyter Mouton. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=604318
Medeiros, K. (2018). R Programming Fundamentals : Deal with Data Using Various Modeling Techniques. Birmingham: Packt Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1904978
Ren, K. (2016). Learning R Programming. Birmingham: Packt Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1409189
Trejo, O., & C. Figliozzi, P. (2017). R Programming By Example : Practical, Hands-on Projects to Help You Get Started with R. Birmingham: Packt Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1682395

Recommended Additional Bibliography

Лучано, Р. Python. К вершинам мастерства / Р. Лучано ; перевод с английского А. А. Слинкин. — Москва : ДМК Пресс, 2016. — 768 с. — ISBN 978-5-97060-384-0. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/93273 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.

Authors

POPOVA DARYA PAVLOVNA

Course Syllabus