Methods

Methods

A profound knowledge in analytical methods has become essential in today’s data-driven world. In academia, PhD programmes and scientific journals require rigorous research that is based on state-of-the-art methods. In industry, an increasing number of positions require practical experience and/or strategic knowledge of sophisticated data analysis.

The important thing is not to stop questioning. Curiosity has its own reason for existing.

~ Albert Einstein

Home

Methods

The important thing is not to stop questioning. Curiosity has its own reason for existing.

~ Albert Einstein

Machine Learning

Teaching computers to learn from experience, more commonly known as machine learning, is already widely used across industries and represents the foundation of any “artificial intelligence” application.

Data visualization

Communicating data in an accurate, efficient, and appealing way is becoming increasingly important, with modern software packages offering powerful data visualization tools that are easy to implement.

Regression analysis

Fundamentals about regression analysis are key for various statistical tests such as analysis of variance and non-parametric tests, and they build the basis for more advanced methods such as machine learning techniques.

Play Video

Instructors regularly teaching research methods for GSERM at different GSERM-destinations are portraying these methods, also explaining which use participants will gain by learning or deepening their knowledge in these methods.

Analyzing Panel Data

Analysts increasingly find themselves presented with data that vary both over cross-sectional units and across time. Such panel data provides unique and valuable opportunities to address substantive questions in the economic, social, and behavioral sciences.

Generative AI with LLMs

GSERM offers a new course @GSERM Ljubljana. Generative AI with LLMs will be taught by Prof. Kunpeng Zhang, Robert H. Smith School of Business, University of Maryland. AI technology, specifically LLMs like GPT-3 and GPT-4, have shown an impressive capacity to generate human-like text. However, understanding and effectively leveraging these models can be a complex task due to their sophisticated architecture and the vast amounts of data they require. This course aims to equip learners with the knowledge and skills to navigate these challenges, demystify the underlying principles of LLMs, and explore practical applications.

Research & Information

We regularly post helpful information and materials related to empirical methods based on our experienced lecturers and beyond. This includes state-of-the-art tools, newly published research, and current trends in qualitative and quantitative methods.