Summary
This three-day hands-on course provides a practical introduction to Artificial Intelligence (AI) and Machine Learning (ML) using Python. Participants learn how to analyse data, build predictive models, evaluate their performance and deploy them in real-world environments.
The training focuses on understanding the full Machine Learning workflow: from collecting and organising data, selecting appropriate algorithms, training and validating models, to deploying lightweight predictive systems. Practical exercises are performed using Python with scikit-learn, and an introduction to neural networks with PyTorch is included.
Prerequisites
Good knowledge of Python programming is required. Experience with Pandas and Jupyter Notebook is an advantage.
Content
- Overview of Artificial Intelligence and Machine Learning
- The Machine Learning workflow: data collection, preparation and deployment
- Working with Data Frames using Pandas
- Supervised versus unsupervised learning
- Training and validation data, cross-validation techniques
- Model evaluation metrics: accuracy, confusion matrix, regression error
- Underfitting versus overfitting, bias-variance trade-off
- Regularisation techniques
- Automated model selection and validation curves
- Regression models: linear regression, polynomial regression, Ridge regression
- Classification models: logistic regression, anomaly detection, decision trees, random forests
- Clustering techniques: K-means
- Dimensionality reduction: PCA and LDA
- Introduction to neural networks and deep learning concepts
- Building and validating models using scikit-learn
- Brief introduction to neural networks with PyTorch
- Deploying trained models for prediction and decision support
Training Method
Classroom-based teaching focused on practical examples and extensive hands-on exercises. Each participant builds and evaluates Machine Learning models during the course.
Course Materials
Provided courseware and practical lab exercises.
Administrative Information
Price 2.255,- € + VAT
Course dates:
21 Apr 2026 - 23 Apr 2026 (Utrecht, NL)
23 Jun 2026 - 25 Jun 2026 (Leuven)
More information
Phone: +32 (0)2 747 47 01
You can find the Full Calendar here.