Data Science - Foundations & Machine Learning

Basic computer skills, knowledge of logic, mathematics, and statistics. Ideally, participants should have completed a data analyst module or equivalent

At the end of the training, participants will be able to:
- Install and use a Python environment for data science
- Manipulate data with fundamental tools (Anaconda, Jupyter, Pandas)
- Master the mathematical foundations necessary for machine learning
- Implement and evaluate different supervised learning models
- Work on artificial neural networks
- Apply unsupervised learning
- Visualise multidimensional data
- Complete a comprehensive data science project and defend it

Software basic programming / Mathematics / Machine Learning / Final Project

Module 1 | Software basic programming |16h
- Anaconda
- Jupyter
- Python

Module 2 | Mathematics | 16h

Module 3 | Machine Learning | 48h
- Introduction Basics concepts and notations
- Basics models for supervised learning
- Multilayer Artificial Neural Networks
- Unsupervised Learning
- Visualising High-dimensional Data

Module 4 | Final Project | 24 h

The approach combines theory, hands-on exercises, and an individual project, with interactive discussions to encourage practical application of the skills learned.

Training Certificate

Cancellation:
In case of cancellation or absence from the course, the registration fees are fully due if the cancellation is not made at least 72 hours before the start of the course. Absences properly justified with a medical certificate entitle the participant to a full refund of the registration fees.