2025/2026
The Digital Economist: Mastering Python for Smarter Analysis
Type:
Mago-Lego
Delivered by:
Department of Educational Programmes
When:
2 module
Open to:
students of all HSE University campuses
Language:
English
Contact hours:
32
Course Syllabus
Abstract
Information Technology (IT) represents an essential change across economic analysis and management decision making. Specific IT tasks allow one to streamline functions including data collection sorting and economic modeling plus future trend prediction. Data analytics tools alongside machine learning systems enable economic experts to tackle complex situations as they analyze policies and reach better data-driven decisions. The fundamental skill that economists need to master in today's industry is Python programming. The programming language Python gained popularity because its beginner-friendly nature along with its flexibility matches up with software libraries Pandas, NumPy, and Matplotlib that enable effective data handling. Python serves as a principal tool for analyzing numbers because its ease of use allows users to automate recurring tasks and process big data and construct predictive models. This Course named "IT for Economists" serves as an educational bridge that connects theoretical economic knowledge to essential IT applications. The course's conclusion yields participants ready to use Python for direct analytics, creating economic models while resolving practical industry problems. By completing this course you'll become more efficient at problem-solving despite also increasing your marketability with employers who value data analysis. When you possess training in IT and Python you gain the ability to convert unprocessed data into valuable management decisions and economic findings that create valuable impacts. The lessons of this course will advance your position in the data-centered sector regardless of your role as student researcher or professional.
Learning Objectives
- Develop Python programming skills for the beginners (economists) with no IT background
- Develop a strong command of Python programming with a focus on economic and business scenarios
- Use Python to manipulate, analyze, and visualize economic and financial datasets effectively
- Build models for economic forecasting, financial analysis, and business decision-making
- Interpret and communicate data insights in an impactful manner
- Apply programming techniques to tackle real-world problems in economics, finance, and management
Expected Learning Outcomes
- Gain proficiency in leveraging Python libraries like NumPy, pandas, Matplotlib, and Seaborn for data analysis in economics and business contexts
- Utilize Python in constructing financial models, performing sensitivity analysis, and optimizing portfolios
- Master Python programming basics, including syntax, data structures, and control flow mechanisms
- Develop regression models and perform time series analysis for economic forecasting and financial planning
- Deliver professional reports and visualizations of economic and financial trends to aid managerial decision-making
Course Contents
- Theoretical basis of economic informatics
- Introduction to basic Statistics and Economic Applications
- Introduction to Python and Economic Applications
- Python programming basic operations
- Data Structures and Control Flow in Economic Models
- NumPy and Matrix Operations in Financial Analytics
- 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
- Python for Financial Decision-Making and Final Project
Bibliography
Recommended Core Bibliography
- Information systems management in practice, McNurlin, B. C., 2004
- Think Python 2ed - CCBY4_077 - Allen B. Downey - 2022 - Open Educational Resources: libretexts.org - https://ibooks.ru/bookshelf/390862 - 390862 - iBOOKS
Recommended Additional Bibliography
- Think Python - How to Think Like a Computer Scientist (Downey) - CCBY4_043 - Allen B. Downey - 2022 - Open Educational Resources: libretexts.org - https://ibooks.ru/bookshelf/390563 - 390563 - iBOOKS