Bachelor
2022/2023
Data Culture
Type:
Elective course (Foreign Languages and Intercultural Communication)
Area of studies:
Linguistics
Delivered by:
Big Data and Information Retrieval School
Where:
School of Foreign Languages
When:
1 year, 3, 4 module
Mode of studies:
distance learning
Online hours:
50
Open to:
students of one campus
Instructors:
Nikita Smirnov
Language:
English
ECTS credits:
3
Contact hours:
40
Course Syllabus
Abstract
This course is aimed at building initial competencies in the field of working with data. The course will cover the basic topics that are required to safely and efficiently use digital technologies and Internet resources. It will also consider tools for scientific research, paper design, presentation of results. In addition, specialized topics related to the application of modern technologies in the humanities will be considered.
Learning Objectives
- This course is an adaptation of two university-wide courses, Digital Literacy and Statistics for Data Analysis, for BA students in Foreign Languages and Intercultural Communication. The course will cover the basic topics that are necessary for the safe and effective use of digital technologies and Internet resources. Tools for conducting research, presentation and publishing of the results will also be considered. In addition, the statistics foundations necessary for research result processing will be considered.
Expected Learning Outcomes
- The ability to collect, process, and analyze data necessary for solving research tasks
- Students will be able to define and critically analyze data cultures within the context of smart city data infrastructure and governance.
Course Contents
- Computer literacy
- 2) Computer security
- Data Cultures and power
- 8) Working with tabular data in MS Excel and Google Spreadsheets
Interim Assessment
- 2022/2023 4th module0.1 * Мини-тесты + 0.25 * КР 1 + 0.2 * Домашние практические работы + 0.25 * КР2 + 0.2 * Групповой проект
Bibliography
Recommended Core Bibliography
- Bernd Held, Theodor Richardson (2015) Microsoft Excel Functions and Formulas, 3rd ed. Mercury Learning. [HSE access, books 24*7]
- Christoph Lindner, & Miriam Meissner. (2019). The Routledge Companion to Urban Imaginaries. Routledge.
- Rockoff, L. (2013). Microsoft Excel 2013 for the Business Analyst. Cengage Learning PTR.
Recommended Additional Bibliography
- Fraser C. Business statistics for competitive advantage with Excel 2016: basics, model building, simulation and cases. New York, NY: Springer Science+Business Media, 2016. 475 с.
- Danielle Stein Fairhurst (2015). Using Excel for Business Analysis
- Keebaik Sim, Woo-Sung Hwang, & Myung-Ryu Choi. (2019). Building a New Smart City: Integrating Local Culture and Technology. Journal of Digital Convergence, 17(9), 193–198. https://doi.org/10.14400/JDC.2019.17.9.193