Courses on artificial intelligence.

Template Course

Data Driven Healthcare

Participants acquire the basic skills to understand and manage biomedical data, including electronic acquisition, storage and exploration using statistical methods.

Introduction to Data Science

The course provides both theoretical and practical training in data science, with a focus on typical machine learning techniques such as clustering, dimensionality reduction, classification, and regression. Students will learn how to interpret inferred models and explain their structure and decisions. Practical exercises are included to reinforce the concepts learned throughout the course.

Coding in Python

During the course, students will be given the tools and knowledge to code in the Python program language.

Text Mining

Computer Vision and Deep Learning

Computer vision is a subfield of AI that seeks to make computers understand the contents of the digital data contained within images or videos and make some sense out of them. Deep learning aims to bring machine learning one step closer to one of its original goals, that is, artificial intelligence.

Advanced Topics in AI

In this course, you will be given an introduction to the basic ideas and techniques which are the basis of the design of intelligent computer systems.

AutoML

The course on "Automated Machine Learning" addresses the challenge of designing well-performing Machine Learning (ML) pipelines, including their hyperparameters, architectures of deep Neural Networks and pre-processing. Future ML developers will learn how to use and design automated approaches for determining such ML pipelines efficiently.