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Обычная версия сайта
2022/2023

Основы программирования

Лучший по критерию «Полезность курса для Вашей будущей карьеры»
Статус: Маго-лего
Когда читается: 2 модуль
Охват аудитории: для своего кампуса
Преподаватели: Попова Дарья Павловна
Язык: английский
Кредиты: 3
Контактные часы: 32

Course 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

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

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

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

Assessment Elements

  • non-blocking Assignment 1
  • non-blocking Assignment 2
  • non-blocking Assignment 3
  • non-blocking Final Project
Interim Assessment

Interim Assessment

  • 2022/2023 2nd module
    0.2 * Assignment 2 + 0.2 * Assignment 3 + 0.2 * Assignment 1 + 0.4 * Final Project
Bibliography

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.