| SYLLABUS | HOURS |
| 1. Python: Initial programming language concepts such as the use of variables, functions, loops, and libraries | 4 |
| 2. Introduction to Machine Learning and its applications | 2 |
| 3. Data Preparation and Exploration: graphs, correlation matrix, detection and treatment of outliers, handling of missing data, data splitting, normalization of variables | 4 |
| 4. Regression and classification models: KNN, Multiple Linear Regression, Random Forest, Support Vector Machine and Artificial Neural Network | 16 |
| 5. Evaluation and optimization of models: performance metrics, hyperparameter tuning, feature selection algorithms | 6 |
| Total | 32 |