Introduction to Python for Data Science

2026/2027

Учебный год

ENG

Обучение ведется на английском языке

4

Кредиты

Кто читает:

Департамент бизнес-информатики и операционного менеджмента

Статус:

Курс обязательный

Когда читается:

2-й курс, 1, 2 модуль

Преподаватели

Гупенко Александр Александрович

Маничев Геннадий Геннадьевич

Омеляш Ксения Васильевна

Course Syllabus

Abstract

Python is an interpreted, high-level, general-purpose programming language. It is suitable for beginners while also being powerful enough to develop complex scripts and applications. This semester course is an introduction to the Python programming language. The average time to complete this course depends on the student’s background. A prerequisite for the course is mathematics at the secondary (high school) level. Students' academic performance is assessed through programming assignments in the form of homework and seminar exercises, oral answers in colloquium, as well as written assessments including midterm test and a final exam. Course assignments practice basic syntax rules, file input and output, and user-defined functions. The course does not include lectures; all theoretical materials are provided to students during practical sessions.

Learning Objectives

• Understand basic syntax rules, data types, and built-in constructs
• Create user-defined functions and work with files
• Become familiar with Python data science libraries: pandas, requests
• Develop basic skills in using Python as an analytical tool

Expected Learning Outcomes

• The student can explain the basic principles of programming in Python
• The student can write scripts to automate processes
• The student can read and understand simple scripts
• The student can identify and fix syntactic and logical errors in scripts
• The student can perform basic exploratory data analysis using Python

Course Contents

• Topic 1. Introduction — Part 1
• Topic 2. Introduction — Part 2
• Topic 3. Basic data types and conditional statements
• Topic 4. Ordered collections — Part 1
• Topic 5. Ordered collections — Part 2
• Topic 6. WHILE loop
• Topic 7. FOR loop
• Topic 8. Unordered collections
• Topic 9. Functions — part 1
• Topic 10. Functions — part 2
• Topic 11. File handling
• Topic 12. Pandas

Assessment Elements

• Graded Seminars
  Given out during seminars. Students individually complete the work during the seminar and submit no later than the end of the session or at the time specified by the teacher. If the student is not present at the class in person during the control element, but has completed an attempt to pass the control element, a score of "0" is given for the corresponding control element. The list of sources allowed for use: - Online translators and dictionaries (with the exception of using built-in image translation functions and built-in chatbot modules with generative artificial intelligence, large language models, etc.); - Searching for information through search engines and usage of specialized websites (including Python documentation and libraries studied in the discipline); - Printed and handwritten notes or copies of lectures and seminars; - Lecture files in .ipynb format. The list of prohibited sources: - Opening and/or usage of messengers, regardless of device and purpose; - Opening and/or usage of chatbots with generative artificial intelligence, deep thinking etc. Presence and/or usage of smartphones (in accordance with clauses 3.5.4.1. and 3.5.4.6. of the Student Internal Regulations at National Research University Higher School of Economics) Other sources not allowed above and leading to violations of student's duties under sub-paragraphs 3.5 of the Student Internal Regulations at National Research University Higher School of Economics. Any graded seminar does not allow retake regardless of absence reasons. The maximum grade for each assignment is 10, including tasks that assess skills exceeding expectations. The assessment is implemented via the SourceCraft version-control based learning environment.
• Colloquium
  The colloquium is held during the last week of each module and covers all topics from the first module (for the first colloquium) and all topics from the first and second modules combined (for the second colloquium) as outlined in the course syllabus. The colloquium consists of two tasks that students are asked to solve orally on their own. The tasks are presented in two formats: – Task 1: explain what the provided code does; – Task 2: discuss how to solve the given problem The colloquium is conducted on a closed-book basis: students are not permitted to have reference materials or use electronic resources during the exam. At the beginning of the colloquium, attendance is taken to verify which students are present. If a student arrives more than 20 minutes late, they receive a "0" for that assessment component. In the event of a violation of the rules, the student will receive a "0" for that assessment component. Duration: 5 minutes. Maximum score for each Colloquium: 5. Retake: Impossible.
• Midterm test
  Midterm covers all topics from the Syllabus (the first module material). Midterm consists of several paper-based tasks. The midterm is open-book: any amount of paper-based materials is allowed (printed or hand-written). During the midterm cheating is strongly prohibited: no additional electronic resources/devices; no talking to peers. In case of the rules violation the student gets zero points for the midterm. Duration: 2 academic hours (80 minutes). Maximum score: 10.
• Exam
  he exam is not blocking. It covers all topics from the course program. Exam covers all topics from the Syllabus. Exam consists of several paper-based tasks. The exam is open-book: any amount of paper-based materials is allowed (printed or hand-written). During the exam cheating is strongly prohibited: no additional electronic resources/devices; no talking to peers. In case of the rules violation the student gets zero points for the exam. Duration: 2 academic hours (80 minutes). Maximum score: 10.

Interim Assessment

• 2026/2027 2nd module
  FG = 0.2 * (C1 + C2) + 0.1 * CW + 0.2 * MT + 0.5 * EX, where: FG — final grade (maximum 10 points); C1 — grade for the first colloquium (maximum 5 points); C2 — grade for the second colloquium (maximum 5 points); CW — arithmetic mean of grades received during the course for assessed seminars (maximum 10 points); MT — grade for the midterm test (maximum 10 points); EX — grade for the final exam (maximum 10 points).

Bibliography

Recommended Core Bibliography

• Python for Everybody - CCBY4_072 - Chuck Severance - 2022 - Open Educational Resources: libretexts.org - https://ibooks.ru/products/390857 - 390857 - iBOOKS

Recommended Additional Bibliography

• Майтак Р.В., Пылов П.А., Протодьяконов А.В. - Python, Django, Data Science - 978-5-9729-2143-0 - Инфра-Инженерия - 2025 - https://znanium.ru/catalog/document?id=469326 - 469326 - ZNANIUM

Authors

• VOLKOVA YULIYA MIKHAYLOVNA
• Orlova Ekaterina Dmitrievna