This recorded introductory course introduces the fascinating world of Machine Learning (ML) to non-experts. It provides a clear and simple overview of how ML works, its real-world applications, and its impact on industries worldwide.

Dr. Vassilis Vassiliades presents how machines are trained to analyze data and make decisions on their own, without being explicitly programmed. Through relatable examples like image recognition, language processing, and personalized recommendations, the session showcases the diverse ways ML is transforming everyday life.

Upon the completion of this course, participants will be able to:

• Describe artificial intelligence and machine learning (ML)
• Compare the traditional approach to programming with the ML approach
• Assess the impact of ML on industries and society, and enumerate specific ML applications
• Distinguish the three main types of ML and provide relevant examples for each
• Outline the stages of the lifecycle of an ML project
• Gain insights into the broader impact of Machine Learning on industries and society.

It is suggested that participants have a basic coding or scripting experience which will make it easier to understand the algorithms presented. However, participants without such experience can also attend the course.

This course is designed to benefit software developers aiming to transition into machine learning, technologists and professionals interested in leveraging machine learning for problem-solving and identifying opportunities, data analysts seeking to enhance their analytical capabilities, and consultants looking to leverage machine learning for providing informed insights and solutions across various industries.

Dr Vassilis Vassiliades is a Research Assistant Professor at the CYENS CoE in Cyprus where he directs the “Cognitive Artificial Intelligence and Robotics” research team. His research explores how software agents and robots efficiently learn, plan and acquire diverse skills in complex environments, often by integrating multimodal sensory data. He received an MSc in Intelligent Systems Engineering from the University of Birmingham, UK (2008), and a PhD in Artificial Intelligence (AI) from the University of Cyprus (2015). He has done post-doctoral work at Inria, France (2015-2018) working on algorithms for efficient damage recovery in robotics. Vassilis has secured more than 2M euros in funding through national, European and industrial projects, and has contributed as a reviewer and author in top-tier conferences and journals on topics related to AI, robotics, machine learning, neural networks, and evolutionary algorithms.