Программирование в Python

Бакалавриат 2023/2024

Статус: Курс обязательный (Программа двух дипломов НИУ ВШЭ и Университета Кёнхи «Экономика и политика в Азии»)

Направление: 41.03.01. Зарубежное регионоведение

Кто читает: Факультет мировой экономики и мировой политики

Где читается: Факультет мировой экономики и мировой политики

Когда читается: 1-й курс, 3, 4 модуль

Формат изучения: без онлайн-курса

Охват аудитории: для своего кампуса

Преподаватели: Карпов Максим Евгеньевич

Язык: английский

Кредиты: 3

Контактные часы: 42

Full Syllabus

Abstract

This is a required course for students of all undergraduate programs at HSE University. The course provides students with basic knowledge of programming for routine tasks automation and data gathering. Via this course, students will also build a solid basis in programming that will be a prerequisite for a statistics course in the second year. The course consists of two parts. In the first part, students will get familiar with basic Python data types and syntax structure. The second part of the course introduces some more complex Python structures and looks into the Python applications for file manipulations. Students achieve excellent results by doing a considerable amount of practical exercises both in class and at home and taking part in group projects.

Learning Objectives

Students achieve excellent results by doing a considerable amount of practical exercises both in class and at home and taking part in group projects

Expected Learning Outcomes

Know and differentiate basic Python data types. Choose the correct data types based on the problem in hand
Know and understand basic Python syntax
Load and use additional Python modules
Solve not complex algorithmic problems using Python
Use cloud-based IDE Google Colaboratory or similar
Use Python for basic data manipulation
Use Python for data gathering and cleaning (web-scraping, parsing)
Use Python for routine tasks automation
Use Python to read and write structured and unstructured files
Write their own functions
Use local-based IDE Jupyter Notebook or similar

Course Contents

Intro and logistics. Jupyter Notebook First program.
Data types: integers and strings. Input and output. Strings formatting.
Data types: floating-point numbers and boolean. Logical operators. Conditionals.
While loop.
Data types: lists and tuples. For loop.
For Loop (2nd Part)
Problem-solving seminar
Methods I (Strings)
Methods II (Lists)
Review I.
MIDTERM
Data types: sets and dictionaries.
Nested Structures
Functions
Working with text files in Python. Regular expressions.
Working with structured files in Python.
Review II
TEST
Web-Scraping I: intro to HTML
Web-Scraping II: simple pages scraping.
Web-Scraping III: news web-site scraping

Assessment Elements

Attendance
Seminar Participation
There will be mini-tasks during the seminars. The student needs to continue the snippet of code on a given task or answer the question. Semi-points and no points are allowed to assess the students' performance. The total grade will be normalised from the maximum in the group.
Homework Assignments
There will be homework assignments devoted to programming basics in Python. Solutions should be submitted via SmartLMS platform. Each assignment will have its own deadline and will be graded from 0 to 10 points. A selective oral examination of a home assignment is performed. In case of plagiarism (or if the student cannot explain his/her solutions), the grades for all homework assignments submitted by the student are zeroed.
Quizzes
There will be 10 short in-class quizzes distributed throughout the course. Each quiz will take 5-10 minutes and will cover the material of the previous weeks (particularities will be communicated at least one week in advance). Question types might be a multiple-choice or a short answer.
Midterm Test
There will be a midterm test at the end of the third module. The test will be conducted via SmartLMS platform. The test will consist of a quiz and a few problems. The midterm test will cover topics up to the Review I. A Mock Test will be published a few weeks in advance.
Final Test
There will be a final test at the beginning of June. The test will be conducted via SmartLMS platform. The test will consist of a quiz and a few problems. The final test will cover the entire course up to Review 2. A Mock Test will be published a few weeks in advance. The grade for the test is from 0 to 10.
Exam (Project Defence)
At the end of the course, students will have to participate in the group project. Groups will consist of 2 students. They will have to gather data from the Internet, write it to a file and then calculate some statistics. Students will have to submit their code and project description before the exam week and then defend it on the day of the exam. Students will be asked questions about the code they have submitted. The total grade will consist of a grade for the written part and a grade for the Q&A part.

Interim Assessment

2023/2024 4th module
min(0.01 * Attendance + 0.2 * Seminar Participation + 0.15 * Homework Assignments + 0.14 * Quizzes + 0.15 * Midterm Test + 0.15 * Final Test + 0.2 * Exam (Project Defence), 8). In accordance with paragraph 69 of the Regulations for Interim and Ongoing Assessments of Students at National Research University Higher School of Economics, grades awarded on the basis of interim assessment outcomes of the discipline-prerequisites for the independent exam on digital competency may not exceed 8 points.

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
Severance, C. (2016). Python for Everybody : Exploring Data Using Python 3. Place of publication not identified: Severance, Charles. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsotl&AN=edsotl.OTLid0000336

Recommended Additional Bibliography

Ivan Idris - Python Data Analysis - Packt Publishing, Limited , 2014-430 - Текст электронный - https://ebookcentral.proquest.com/lib/hselibrary-ebooks/detail.action?docID=1826990

Course Syllabus