(in Polish) R i Python w finansach 2600-FCz1RPF

The course introduces participants to working environments in R and Python, the installation of external packages, and the fundamentals of using scripts written in these languages. It covers popular functions, data analysis tools, and methods for presenting results. Students will acquire techniques for handling datasets, as well as the basics of object-oriented programming, data structures, and functions. By the end of the course, participants will have gained the skills necessary to work with digital finance data in R and Python. In addition to in-class sessions, students will complete a project related to digital finance.
Topics Covered
• Installation of software and libraries, using the interface, basic operations, and creating and saving scripts.
• Basic functions and objects, syntax essentials, and commenting in scripts.
• Importing and exporting data in common formats and preparing it for analysis.
• Working with real datasets and fundamental principles of data cleaning.
• Loops and conditional statements.
• Basics of writing functions.
• Data visualization using core graphics libraries.
• Descriptive statistics.
• Correlation analysis and Student’s t-test.
• Simple and multiple regression: conducting analyses and checking assumptions.
• Cluster analysis.
• Preparing and presenting basic quantitative analyses in the field of digital finance.
Student Workload
• 30 hours of in-class sessions.
• 30 hours of independent work on practical assignments.
• 30 hours of final project preparation.
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K_W01 – Demonstrates an advanced understanding of research methodology and terminology in the discipline of economics and finance, as well as in complementary disciplines (management and quality sciences, and legal sciences).
K_W05 – Understands complex technological, social, political, legal, economic, and ecological processes and phenomena, including the fundamental dilemmas of contemporary civilization, and their impact on financial decision-making in organizations, the functioning of the economy, and the development of information systems.
K_U03 – Selects appropriate sources and adapts existing methods or develops new ones, including advanced information and communication technologies, to identify, diagnose, and solve problems related to financial decision-making in the field of digital finance.
K_U04 – Formulates and tests hypotheses related to research problems presented.
K_U06 – Independently and in teams prepares analyses, diagnoses, and reports on complex and atypical problems in digital finance within organizations; effectively presents findings to diverse audiences; and engages in debate, including in English, using advanced information and communication tools.
K_K01 – Demonstrates the ability to assess and critically approach complex situations and phenomena related to digital finance in organizations.
K_K02 – Recognizes the significance and value of scientific knowledge in addressing complex problems in digital finance within organizations and seeks expert opinions in the problem-solving process.