Bachelor
2026/2027
External Examinations on Digital Skills. Final Level
Type:
Compulsory course (HSE University and Kyung Hee University Double Degree Programme in Economics and Politics in Asia)
Delivered by:
Digital Skills Development Unit
Where:
Faculty of Computer Science
When:
3 year, 2 module
Open to:
students of all HSE University campuses
Language:
English
Contact hours:
2
Course Syllabus
Abstract
The External Assessment of Digital Competencies (EADC) is embedded in all HSE University degree programmes and is mandatory for second-year undergraduate students enrolled in Russian-taught programmes. The EADC Final Assessment determines the student's final level of digital competency attainment.
The EADC Final Assessment is administered using proctoring procedures and lasts 180 minutes. It comprises a test component and a practical component. In the practical component, students address a problem scenario by selecting one of several possible courses of action.
The final result is converted to a 1-10 scale. Scores below 4 are rounded down by discarding the decimal part; scores of 4 or above are rounded to the nearest whole number. Failure to obtain a passing result in the External Assessment of Digital Competencies within the prescribed timeframe does not give rise to academic debt. However, failure to take the assessment is treated as academic debt until the assessment has been completed.
Learning Objectives
- To determine the student’s final level of digital competence through test-based and practical assignments.
Expected Learning Outcomes
- The student is able to apply digital competencies to analyse problem situations and select a well-reasoned course of action.
Assessment Elements
- Part AThe test component comprises eight items, which may include multiple-choice questions, short-answer items, code-ordering tasks, and similar formats.
- Part B
- Part C
Bibliography
Recommended Core Bibliography
- 9781491912140 - Vanderplas, Jacob T. - Python Data Science Handbook : Essential Tools for Working with Data - 2016 - O'Reilly Media - https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1425081 - nlebk - 1425081
- Vanderplas, J.T. (2016). Python data science handbook: Essential tools for working with data. Sebastopol, CA: O’Reilly Media, Inc. https://proxylibrary.hse.ru:2119/login.aspx?direct=true&db=nlebk&AN=1425081.
Recommended Additional Bibliography
- A Tutorial on Machine Learning and Data Science Tools with Python. (2017). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.E5F82B62
- Baesens, B. (2014). Analytics in a Big Data World : The Essential Guide to Data Science and Its Applications. Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=761032
- Kotu, V., & Deshpande, B. (2019). Data Science : Concepts and Practice (Vol. Second edition). Cambridge, MA: Morgan Kaufmann. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1866160