Python: Introduction to Machine Learning

Machine Learning (ML), a key subfield of Artificial Intelligence, is increasingly used across domains such as government, healthcare, education, marketing, business, and life sciences. By leveraging historical data, ML models can identify patterns and predict outcomes for new, unseen data.

In this practical, hands-on course, participants learn how to build their own ML models in Python and apply them to real-world problems. The course covers core ML concepts and a simplified data science workflow, including supervised, unsupervised, and basic reinforcement learning techniques. For their final project, participants will design and implement an end-to-end ML workflow using a provided dataset.