Statistics and elements of AI in scientific research ERASMUS>EKO20

The course "Statistics and Elements of AI in Scientific Research" offers a robust foundation in both descriptive and mathematical statistics, alongside an introduction to key artificial intelligence concepts. In the realm of statistics, students will delve into descriptive statistics, learning how to summarize and interpret data effectively through measures such as mean, median, mode, and standard deviation. Additionally, the course covers statistical inference, equipping students with the tools to draw conclusions about populations based on sample data, including hypothesis testing and confidence intervals. On the AI front, the course introduces fundamental methodologies, including machine learning, supervised and unsupervised learning, and explores how these techniques can be applied in scientific research. A particular emphasis is placed on the integration of advanced statistical methods with AI, specifically within the domains of economics and finance. Through this comprehensive approach, students will develop the skills necessary to apply both statistical analysis and AI tools in solving complex research problems, making data-driven decisions, and advancing knowledge in their fields.