Learning Targets:

After successful completion of the course, students are able to:

• Analyze and apply advanced data analysis methods;
• Describe and apply selected artificial intelligence methods;
• Formulate domain-specific problems (e.g., auditing, economics, finance, logistics) as artificial intelligence tasks and develop appropriate solution approaches;
• Implement core artificial intelligence techniques using Python and relevant libraries; 
• Critically evaluate and interpret model performance using appropriate evaluation metrics and validation methodologies.

Outline:

1. Advanced data analysis methods
2. Fundamentals of artificial intelligence
3. Deep learning
4. Text mining and natural language processing
5. Generative AI and large language models
6. Interpretability

Methods of Assessment:

Exam, Duration: 60 minutes. Bonus point (quizzes).