Artificial Intelligence (AI) has grown in the last few years from a promising research field into a widely applied technology. Many processes and decisions in our lives are governed by algorithms: from autonomous driving, e-commerce recommendations, traffic predictions to fraud detection. It is important that AI is used correctly, to prevent privacy issues, discriminations and other harm. In this course we explain what AI is, how algorithms work, and how you select, train and implement algorithms.
In this course you get a hands-on introduction into all aspects of modern AI. You will learn the following:
- Definition of AI and common usage. Distinction between AI, machine learning, deep learning and classic AI;
- Explanation of rule based systems and limitations;
- Representing data as vectors and manipulating data with linear algebra in python;
- Neural networks;
- Genetic Algorithms;
- The process of training, testing and evaluating algorithms;
- Understanding algorithmic bias and how to ensure the ethical and responsible use of AI.
The course consists of a combination of lectures, practical sessions using the Python programming language, and group discussions.
Lecturers
- Dr. Stefan Leijnen, Professor AI
- Sieuwert van Otterloo, PhD
Target audience
Bachelor and Master students from all background are welcome. It is necessary to have basic mathematics experience (linear algebra) and computer literacy skills. The course includes practical sessions where students will use Python and Jupyter notebook to complete assignments. Note that students should bring their own laptop computer.
Aim of the course
The aim of the course is to give students with a Business or Science background an understanding of Artificial Intelligence and help them develop basic AI systems.
Study load
40 Hours