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Development of Linguistic Systems

2022/2023
Academic Year
ENG
Instruction in English
3
ECTS credits
Delivered at:
School of Fundamental and Applied Linguistics
Course type:
Compulsory course
When:
4 year, 1, 2 module

Course Syllabus

Abstract

This course is designed to introduce students to various professions, such as technical writer, program manager, analytic and program developer, that are most often found in various IT companies. Skills acquired during the entire period of study and during the acquisition of the discipline will help students to try themselves as specialists in several areas. It will help them with choosing a profession after graduation.
Learning Objectives

Learning Objectives

  • ● The purpose of the course is to teach students how to use computer technologies (primarily the Python programming language) to solve linguistic problems that arise in practice, as well as apply existing linguistic knowledge to compose technical documentation and conduct text analytics.
Expected Learning Outcomes

Expected Learning Outcomes

  • The student writes technical documentation
  • The student is able to correctly label data
  • The student is able to analyze data using modern computer tools
  • The student is able to write dialogue scripts for chatbots, as well as put them into practice
  • The student is able to work in a team and distribute the load among team members
  • A student as part of a team is able to interact with both “technical” and “linguistic” teams within the same project
Course Contents

Course Contents

  • Acquiring technical writing skills
  • Acquiring data labeling skills
  • Acquiring data analytics skills
  • Acquiring developer-linguist skills
  • Acquiring project manager skills
  • Modeling of language start-up
Assessment Elements

Assessment Elements

  • non-blocking Homework module 1
  • non-blocking Homework module 2
Interim Assessment

Interim Assessment

  • 2022/2023 2nd module
    0.5 * Homework module 1 + 0.5 * Homework module 2
Bibliography

Bibliography

Recommended Core Bibliography

  • Dipanjan Sarkar. (2019). Text Analytics with Python : A Practitioner’s Guide to Natural Language Processing: Vol. Second edition. Apress.

Recommended Additional Bibliography

  • Joseph Heagney. (2016). Fundamentals of Project Management: Vol. Fifth edition. AMACOM.