Программирование в Python

Бакалавриат 2022/2023

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, Перевышина Татьяна Олеговна, Тарасенко Георгий Константинович

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

Homework Project (Individual)
There will be an individual homework project in the middle of the course where each student will have to write a code that solves the given problem and follows the provided guidelines. The project is graded from 0 to 10, and will count towards the final grade with a weight of 15%
Work in Class
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.
Take-home Problem sets
There will be ten homework assignments with Python problems sets. Solutions should be submitted via SmartLMS platform and graded automatically. Each assignment will have its own deadline and will be graded from 0 to 10 points. The mean of all assignments will count towards the final grade with a weight of 15%.
Quizzes
There will be 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. The sum of all grades will count towards the final grade with a weight of 15%.
Midterm test
There will be a midterm test at the end of the third module and the test in the beginning of June. Both will be conducted via SmartLMS platform. The tests will consist of a quiz and a few problems. The midterm test will cover topics up to the Review I. The test will cover the entire course up to Review 2. For each test, a Mock Test will be published a few weeks in advance. If the test were to be conducted online the students will have to share their screens and turn on your camera during it. Failure to do so will result in grade 0 for the assignment. The grade for each test is from 0 to 10. The average of two tests will count towards the final grade with a weight of 30%.
Final Test
There will be a midterm test at the end of the third module and the test in the beginning of June. Both will be conducted via SmartLMS platform. The tests will consist of a quiz and a few problems. The midterm test will cover topics up to the Review I. The test will cover the entire course up to Review 2. For each test, a Mock Test will be published a few weeks in advance. If the test were to be conducted online the students will have to share their screens and turn on your camera during it. Failure to do so will result in grade 0 for the assignment. The grade for each test is from 0 to 10. The average of two tests will count towards the final grade with a weight of 30%.
Final Group Project (2 people)
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 via Python, write it to a file and then calculate some statistics. Students will have to submit their code and project description during 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. All students in the group receive the Q&A grade based on the performance of the weakest student in the group (e.g. if one of the participants cannot answer any question, then the entire group gets a 0 for a defence part). Particularities of the project will be announced in the second part of the 4th module. The project grade will count towards the final grade with a weight of 10%.

Interim Assessment

2022/2023 4th module
0.15 * Take-home Problem sets + 0.15 * Work in Class + 0.15 * Midterm test + 0.15 * Homework Project (Individual) + 0.15 * Quizzes + 0.15 * Final Test + 0.1 * Final Group Project (2 people)

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