Бакалавриат
2022/2023
Python программирование и обработка данных
Статус:
Курс обязательный (Международная программа по экономике и финансам)
Направление:
38.03.01. Экономика
Кто читает:
Международный институт экономики и финансов
Где читается:
Международный институт экономики и финансов
Когда читается:
1-й курс, 3 модуль
Формат изучения:
без онлайн-курса
Охват аудитории:
для своего кампуса
Язык:
английский
Кредиты:
4
Контактные часы:
44
Course Syllabus
Abstract
a. Pre-requisites
Primary school knowledge in computer science
b. Abstract
In the modern, highly technological world computer skills have become essential for specialists in all fields. Programming in particular has gone beyond its traditional borders of being just a prerogative of IT specialists, turning into an element of computer literacy. In the last 10 years programming languages and tools have evolved significantly, which now enables people even without a solid technical background to successfully master related skills.
The main part of the course is focused on programming and data processing techniques using the Python language. It is complemented by a blended part on Excel, featuring data processing techniques that can be useful in later ICEF courses and economics-related applications. The course is not part of the University of London international programme.
Learning Objectives
- Although based on a particular toolset (Python), the course aims to give a broad perspective of what can be done using a modern general-purpose programming language.
- On course completion, students should be: • able to work with information: to find, evaluate and use information from various sources, necessary to solve scientific and professional problems (including those on the basis of a systematic approach)
- • capable of working in a team
- • able to solve analytical and research problems with modern technical means and information technology;
- • able to use modern technical means and information technologies for solving communicative tasks;
Expected Learning Outcomes
- Work with basic data structures of programming languages
- Apply several techniques of automated data acquisition including API queries, methods of processing structured and unstructured data
Course Contents
- Digital literacy
- Topic 1. Python Language Basic
- Topic 2. Logical data type and conditional statements
- Topic 3. For Loop and While loop
- Topic 4. Data structures
- Topic 5. Methods
- Topic 6. Nested data structures. Sorting
- Topic 7. Functions
- Topic 8. Text files and tables
Interim Assessment
- 2022/2023 3rd module0.1 * home assignments + 0.75 * exam + 0.15 * Test in digital literacy
Bibliography
Recommended Core Bibliography
- Ben Stephenson. (2019). The Python Workbook : A Brief Introduction with Exercises and Solutions (Vol. 2nd ed. 2019). Springer.
- Downey, A. (2015). Think Python : How to Think Like a Computer Scientist (Vol. Second edition). Sebastopol, CA: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1105725
Recommended Additional Bibliography
- McKinney, W. (2012). Python for Data Analysis : Data Wrangling with Pandas, NumPy, and IPython. Sebastopol, CA: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=495822