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Technical data analysis

General data

Course ID:	3201-LST-TDA
Erasmus code / ISCED:	(unknown) / (unknown)
Course title:	Technical data analysis
Name in Polish:	Technical data analysis
Organizational unit:	Institute of Applied Linguistics
Course groups:
ECTS credit allocation (and other scores):	3.00 Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load.
Language:	English
Type of course:	obligatory courses
Mode:	Classroom
Short description:	The aim of the course is to teach students how to technically process data using digital humanities tools and dedicated software. Students will learn about regular expressions (Regex) and the use of artificial intelligence (intelligent browsing, chatGPT, etc.) when working on data analysis and preparing databases and their descriptions.
Learning outcomes:	Knowledge: the graduate knows and understands: -in-depth, specialized terminology in the fields of theoretical linguistics, corpus linguistics, neuroscience -in-depth, the main directions of development and contemporary research trends in linguistics (theoretical, computational, cognitive, corpus, social/text linguistics) and knows where the most important linguistic research centers in Europe and the world are located -in-depth, research methods used in: psycholinguistics, neurolinguistics, corpus linguistics, digital linguistics and text linguistics, as well as statistical models Skills: the graduate is able to: -use in-depth theoretical and practical knowledge to carry out research work and solve complex problems in linguistics (theoretical, computational, cognitive, corpus, social/text linguistics) using appropriate methodology -use advanced research tools of linguistics (theoretical, computational, cognitive, corpus-based) and select research methods appropriately to the problems undertaken -use in-depth knowledge of linguistics (theoretical, computational, cognitive, corpus-based, social/text linguistics) through the selection and appropriate application of modern information and communication technology (including statistical, corpus, eye-tracking and EEG analysis software) when working with research data Social competences: the graduate is ready to: -recognize the importance of the latest linguistic knowledge and critically evaluate research in linguistics (theoretical, computational, cognitive, corpus, social/text linguistics), especially those published in scientific journals and monographs and popular science sources -recognize the importance of linguistic knowledge in solving cognitive and practical problems and to consult with experts -initiate and carry out linguistic research, in particular to improve accessibility in the dimensions of language, information and communication

Classes in period "Winter semester 2024/25" (future)

Time span:	2024-10-01 - 2025-01-26	Selected timetable range: weekly course term Navigate to timetable
Type of class:	Classes, 30 hours more information
Coordinators:	Karolina Broś
Group instructors:	(unknown)
Students list:	(inaccessible to you)
Examination:	Course - Examination Classes - Examination

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Copyright by University of Warsaw.