1. Introduction to intelligent data analysis

2. Introduction to data processing in Python

3. Exploratory analysis and data visualization

4. Getting and linking data

5. Exploratory analysis using statistical analysis

6. Data cleaning and preprocessing

7. Preprocessing of textual data

8. Evaluation and model selection

9. Linear and logistic regression

10. Decision trees

11. Numerical optimization and simulations

12. Advanced data analysis topics 

Type of methodology: Combination of lecture and hands-on

Participants receive the certificate of attendance: Yes

Paid training activity for participants: Yes, for all

Participants prerequisite knowledge: Numerical methods (linear algebra, statistics) Domain-specific background knowledge