Understand in depth concepts and terminology of machine learning and data science.

Comprehend the biases that may exist in machine learning models and how to address them.

Recognize algorithmic applications and uncover pitfalls and biases in models, identifying them in generated texts.

Understand why Large Language Models (LLMs) produce incorrect content and how to detect and correct such errors.

Know various algorithms developed for computational journalism, such as natural language processing and machine learning.

Deeply understand best practices for writing, documenting, and publishing algorithms and code, promoting transparency.

Analyze data using linear regression, clustering, text mining, natural language processing, decision trees, machine learning tools, and methods.