Основы Python для экономистов (курс для начинающих)

2026/2027

Статус: Маго-лего

Кто читает: Департамент образовательных программ

Где читается: Институт статистических исследований и экономики знаний

Охват аудитории: для всех кампусов НИУ ВШЭ

Язык: русский

Кредиты: 3

Контактные часы: 32

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Аннотация

The growing importance of data-driven decision-making has transformed the field of economics, making basic programming and data analysis skills essential. Python has emerged as the leading programming language for economic analysis due to its simplicity, readability, and powerful analytical libraries. Python Fundamentals for Economists (A Beginner’s Course), is an introductory, practice-oriented course. The course starts from the very basics of computing and programming, assuming no prior experience, and gradually builds students’ confidence in using Python for economic and business analysis. Participants will learn how to write simple Python programs, work with economic data, perform basic statistical analysis, and create clear visualizations. Emphasis is placed on understanding fundamental programming concepts and applying them to real-world economic problems. By the end of the course, students will be able to use Python as a practical analytical tool.

Цель освоения дисциплины

Develop Python programming skills for the beginners (economists) with no IT background
Write simple and readable Python programs using fundamental syntax and logic
Develop understanding of Basic Python programming with a focus on economic and business scenarios
Manipulate, analyze, and summarize simple economic datasets using beginner-friendly tools
Build confidence in using Python for further learning in econometrics, finance, and data analysis

Планируемые результаты обучения

Demonstrate understanding of Python programming fundamentals, including variables, data types, operators, and control flow
Ability to use basic Python data structures (lists, dictionaries, tuples) to store and manage economic data
Perform introductory data analysis using NumPy and pandas at a beginner level
Create basic visualizations using Matplotlib and Seaborn to illustrate economic trends
Apply simple regression and time-series concepts using Python tools with guided instruction
Communicate economic insights clearly through beginner-level analytical reports and visual outputs

Содержание учебной дисциплины

Theoretical basis of economic informatics
Introduction to basic Statistics and Economic Applications
Introduction to Python and Economic Applications
Introduction to Python Basics: Data Types, Operators, and Simple Logic
Basic Data Structures and Simple Economic Simulations
Introduction to NumPy and its simple applications
Introduction to Data Analysis with pandas for Economic Datasets
Data Visualization for Economic Insights
Basic Regression Models for Economic Forecasting
Time Series Analysis for Finance and Economics
Introduction to the Concept of Blockchains and Python Applications

Элементы контроля

In-class assignment
In-class Assignment can be a Research Article/ Report, based on your master program thesis or planned future topic. Assignments not submitted within the stipulated deadline will be marked as incomplete unless valid reasons (with supporting documentation) are provided. Students must actively participate in in-class activities and discussions.
Project
To pass, students must demonstrate and present a topic related to recent trends such as AI, Smart Cities, Internet of Thing, Smart Economics, Usage of AI in transforming markets and economy etc. Students should understand and present a real-world problem they have chosen, and their presentation should effectively showcase the application of analysis, visualization techniques, providing well-structured insights and actionable recommendations.
Exam
To successfully pass the course, students must demonstrate competency through both a written and an oral examination. The written exam will evaluate their ability to write, debug, and optimize Python code, as well as apply studied core concepts such as data structures, control flow, and library utilization to solve economics and business related problems. The oral exam will assess their conceptual understanding of IT for economics, ability to articulate coding solutions, and application of Python to practical scenarios in a clear and professional manner.

Промежуточная аттестация

2026/2027 2nd module
0.4 * Exam + 0.3 * In-class assignment + 0.3 * Project

Список литературы

Авторы

Андраби Умер Мукхтар

Программа дисциплины